def test_block_densenet(system_dict):
forward = True;
test = "test_block_densenet";
system_dict["total_tests"] += 1;
print_start(test, system_dict["total_tests"])
if(forward):
try:
gtf = prototype(verbose=0);
gtf.Prototype("sample-project-1", "sample-experiment-1");
network = [];
network.append(gtf.densenet_block(bottleneck_size=4, growth_rate=16, dropout=0.2));
gtf.Compile_Network(network, data_shape=(1, 64, 64), use_gpu=False);
x = torch.randn(1, 1, 64, 64);
y = gtf.system_dict["local"]["model"](x);
system_dict["successful_tests"] += 1;
print_status("Pass");
except Exception as e:
system_dict["failed_tests_exceptions"].append(e);
system_dict["failed_tests_lists"].append(test);
forward = False;
print_status("Fail");
else:
system_dict["skipped_tests_lists"].append(test);
print_status("Skipped");
return system_dict
def test_block_inception_a(system_dict):
forward = True;
test = "test_block_inception_a";
system_dict["total_tests"] += 1;
print_start(test, system_dict["total_tests"])
if(forward):
try:
gtf = prototype(verbose=0);
gtf.Prototype("sample-project-1", "sample-experiment-1");
network = [];
network.append(gtf.inception_a_block(pooling_branch_channels=32, pool_type="avg"));
network.append(gtf.inception_a_block(pooling_branch_channels=32, pool_type="max"));
gtf.Compile_Network(network, data_shape=(1, 64, 64), use_gpu=False);
x = torch.randn(1, 1, 64, 64);
y = gtf.system_dict["local"]["model"](x);
system_dict["successful_tests"] += 1;
print_status("Pass");
except Exception as e:
system_dict["failed_tests_exceptions"].append(e);
system_dict["failed_tests_lists"].append(test);
forward = False;
print_status("Fail");
else:
system_dict["skipped_tests_lists"].append(test);
print_status("Skipped");
return system_dict
def test_loss_sigmoid_binary_crossentropy(system_dict):
forward = True;
test = "test_loss_sigmoid_binary_crossentropy";
system_dict["total_tests"] += 1;
print_start(test, system_dict["total_tests"])
if(forward):
try:
gtf = prototype(verbose=0);
gtf.Prototype("sample-project-1", "sample-experiment-1");
label = torch.empty((1, 5)).random_(2);
y = torch.randn(1, 5);
gtf.loss_sigmoid_binary_crossentropy();
load_loss(gtf.system_dict);
loss_obj = gtf.system_dict["local"]["criterion"];
loss_val = loss_obj(y, label);
system_dict["successful_tests"] += 1;
print_status("Pass");
except Exception as e:
system_dict["failed_tests_exceptions"].append(e);
system_dict["failed_tests_lists"].append(test);
forward = False;
print_status("Fail");
else:
system_dict["skipped_tests_lists"].append(test);
print_status("Skipped");
return system_dict
def test_block_resnet_v2_bottleneck(system_dict):
forward = True;
test = "test_block_resnet_v2_bottleneck";
system_dict["total_tests"] += 1;
print_start(test, system_dict["total_tests"])
if(forward):
try:
gtf = prototype(verbose=0);
gtf.Prototype("sample-project-1", "sample-experiment-1");
network = [];
network.append(gtf.resnet_v2_bottleneck_block(output_channels=32, stride=1, downsample=True));
network.append(gtf.resnet_v2_bottleneck_block(output_channels=32, stride=1, downsample=False));
gtf.Compile_Network(network, data_shape=(1, 64, 64), use_gpu=False);
x = torch.randn(1, 1, 64, 64);
y = gtf.system_dict["local"]["model"](x);
system_dict["successful_tests"] += 1;
print_status("Pass");
except Exception as e:
system_dict["failed_tests_exceptions"].append(e);
system_dict["failed_tests_lists"].append(test);
forward = False;
print_status("Fail");
else:
system_dict["skipped_tests_lists"].append(test);
print_status("Skipped");
return system_dict
def test_activation_rrelu(system_dict):
forward = True;
test = "test_activation_rrelu";
system_dict["total_tests"] += 1;
print_start(test, system_dict["total_tests"])
if(forward):
try:
gtf = prototype(verbose=0);
gtf.Prototype("sample-project-1", "sample-experiment-1");
network = [];
network.append(gtf.rrelu());
gtf.Compile_Network(network, data_shape=(3, 64, 64), use_gpu=False);
x = torch.randn(1, 3, 64, 64);
y = gtf.system_dict["local"]["model"](x);
system_dict["successful_tests"] += 1;
print_status("Pass");
except Exception as e:
system_dict["failed_tests_exceptions"].append(e);
system_dict["failed_tests_lists"].append(test);
forward = False;
print_status("Fail");
else:
system_dict["skipped_tests_lists"].append(test);
print_status("Skipped");
return system_dict
def test_loss_kldiv(system_dict):
forward = True
test = "test_loss_kldiv"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
gtf = prototype(verbose=0)
gtf.Prototype("sample-project-1", "sample-experiment-1")
label = torch.randn(1, 5)
y = torch.randn(1, 5)
gtf.loss_kldiv()
load_loss(gtf.system_dict)
loss_obj = gtf.system_dict["local"]["criterion"]
loss_val = loss_obj(y, label)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
return system_dict
def test_optimizer_momentum_rmsprop(system_dict):
forward = True;
if(not os.path.isdir("datasets")):
os.system("! wget --load-cookies /tmp/cookies.txt \"https://docs.google.com/uc?export=download&confirm=$(wget --save-cookies /tmp/cookies.txt --keep-session-cookies --no-check-certificate 'https://docs.google.com/uc?export=download&id=1rG-U1mS8hDU7_wM56a1kc-li_zHLtbq2' -O- | sed -rn 's/.*confirm=([0-9A-Za-z_]+).*/\1\n/p')&id=1rG-U1mS8hDU7_wM56a1kc-li_zHLtbq2\" -O datasets.zip && rm -rf /tmp/cookies.txt")
os.system("! unzip -qq datasets.zip")
test = "test_optimizer_momentum_rmsprop";
system_dict["total_tests"] += 1;
print_start(test, system_dict["total_tests"])
if(forward):
try:
gtf = prototype(verbose=0);
gtf.Prototype("sample-project-1", "sample-experiment-1");
gtf.Default(dataset_path="datasets/dataset_cats_dogs_train",
model_name="resnet18", freeze_base_network=True, num_epochs=2);
gtf.optimizer_momentum_rmsprop(0.01, weight_decay=0.0001, decay_rate=0.9);
gtf.Train();
system_dict["successful_tests"] += 1;
print_status("Pass");
except Exception as e:
system_dict["failed_tests_exceptions"].append(e);
system_dict["failed_tests_lists"].append(test);
forward = False;
print_status("Fail");
else:
system_dict["skipped_tests_lists"].append(test);
print_status("Skipped");
return system_dict
def test_layer_transposed_convolution2d(system_dict):
forward = True
test = "test_layer_transposed_convolution2d"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
gtf = prototype(verbose=0)
gtf.Prototype("sample-project-1", "sample-experiment-1")
network = []
network.append(
gtf.transposed_convolution2d(output_channels=3, kernel_size=3))
gtf.Compile_Network(network,
data_shape=(3, 128, 128),
use_gpu=False)
x = torch.randn(1, 3, 128, 128)
y = gtf.system_dict["local"]["model"](x)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
return system_dict
def test_activation_softmin(system_dict):
forward = True
test = "test_activation_softmin"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
gtf = prototype(verbose=0)
gtf.Prototype("sample-project-1", "sample-experiment-1")
network = []
network.append(gtf.softmin())
gtf.Compile_Network(network, data_shape=(3, 64, 64), use_gpu=False)
x = torch.randn(1, 3, 64, 64)
y = gtf.system_dict["local"]["model"](x)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
return system_dict
def test_block_resnext(system_dict):
forward = True
test = "test_block_resnext"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
gtf = prototype(verbose=0)
gtf.Prototype("sample-project-1", "sample-experiment-1")
network = []
network.append(
gtf.resnext_block(output_channels=256,
cardinality=8,
bottleneck_width=4,
stride=1,
downsample=True))
network.append(
gtf.resnext_block(output_channels=256,
cardinality=8,
bottleneck_width=4,
stride=1,
downsample=False))
gtf.Compile_Network(network, data_shape=(1, 64, 64), use_gpu=False)
x = torch.randn(1, 1, 64, 64)
y = gtf.system_dict["local"]["model"](x)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
return system_dict
def test_analyse(system_dict):
forward = True;
if(not os.path.isdir("datasets")):
os.system("! wget --load-cookies /tmp/cookies.txt \"https://docs.google.com/uc?export=download&confirm=$(wget --save-cookies /tmp/cookies.txt --keep-session-cookies --no-check-certificate 'https://docs.google.com/uc?export=download&id=1rG-U1mS8hDU7_wM56a1kc-li_zHLtbq2' -O- | sed -rn 's/.*confirm=([0-9A-Za-z_]+).*/\1\n/p')&id=1rG-U1mS8hDU7_wM56a1kc-li_zHLtbq2\" -O datasets.zip && rm -rf /tmp/cookies.txt")
os.system("! unzip -qq datasets.zip")
test = "analyse_object_creation";
system_dict["total_tests"] += 1;
print_start(test, system_dict["total_tests"])
if(forward):
try:
ptf = prototype(verbose=0);
system_dict["successful_tests"] += 1;
print_status("Pass");
except Exception as e:
system_dict["failed_tests_exceptions"].append(e);
system_dict["failed_tests_lists"].append(test);
forward = False;
print_status("Fail");
else:
system_dict["skipped_tests_lists"].append(test);
print_status("Skipped");
test = "analyse_Prototype()";
system_dict["total_tests"] += 1;
print_start(test, system_dict["total_tests"])
if(forward):
try:
ptf.Prototype("sample-project-1", "sample-experiment-1");
system_dict["successful_tests"] += 1;
print_status("Pass");
except Exception as e:
system_dict["failed_tests_exceptions"].append(e);
system_dict["failed_tests_lists"].append(test);
forward = False;
print_status("Fail");
else:
system_dict["skipped_tests_lists"].append(test);
print_status("Skipped");
test = "analyse_Default()";
system_dict["total_tests"] += 1;
print_start(test, system_dict["total_tests"])
if(forward):
try:
ptf.Default(dataset_path="datasets/dataset_cats_dogs_train",
model_name="resnet18", freeze_base_network=True, num_epochs=2);
system_dict["successful_tests"] += 1;
print_status("Pass");
except Exception as e:
system_dict["failed_tests_exceptions"].append(e);
system_dict["failed_tests_lists"].append(test);
forward = False;
print_status("Fail");
else:
system_dict["skipped_tests_lists"].append(test);
print_status("Skipped");
test = "analyse_Analyse_Learning_Rates()";
system_dict["total_tests"] += 1;
print_start(test, system_dict["total_tests"])
if(forward):
try:
analysis_name = "analyse_learning_rates"
lrs = [0.1, 0.05];
epochs=2
percent_data=40
analysis = ptf.Analyse_Learning_Rates(analysis_name, lrs, percent_data, num_epochs=epochs, state="keep_none");
system_dict["successful_tests"] += 1;
print_status("Pass");
except Exception as e:
system_dict["failed_tests_exceptions"].append(e);
system_dict["failed_tests_lists"].append(test);
forward = False;
print_status("Fail");
else:
system_dict["skipped_tests_lists"].append(test);
print_status("Skipped");
test = "analyse_Analyse_Input_Sizes()";
system_dict["total_tests"] += 1;
print_start(test, system_dict["total_tests"])
if(forward):
try:
analysis_name = "analyse_input_sizes";
input_sizes = [128, 256];
epochs=2;
percent_data=40;
analysis = ptf.Analyse_Input_Sizes(analysis_name, input_sizes, percent_data, num_epochs=epochs, state="keep_none");
system_dict["successful_tests"] += 1;
print_status("Pass");
except Exception as e:
system_dict["failed_tests_exceptions"].append(e);
system_dict["failed_tests_lists"].append(test);
forward = False;
print_status("Fail");
else:
system_dict["skipped_tests_lists"].append(test);
print_status("Skipped");
test = "analyse_Analyse_Batch_Sizes()";
system_dict["total_tests"] += 1;
print_start(test, system_dict["total_tests"])
if(forward):
try:
analysis_name = "analyse_batch_sizes";
batch_sizes = [2, 3];
epochs = 2;
percent_data = 40;
analysis = ptf.Analyse_Batch_Sizes(analysis_name, batch_sizes, percent_data, num_epochs=epochs, state="keep_none");
system_dict["successful_tests"] += 1;
print_status("Pass");
except Exception as e:
system_dict["failed_tests_exceptions"].append(e);
system_dict["failed_tests_lists"].append(test);
forward = False;
print_status("Fail");
else:
system_dict["skipped_tests_lists"].append(test);
print_status("Skipped");
test = "analyse_Analyse_Models()";
system_dict["total_tests"] += 1;
print_start(test, system_dict["total_tests"])
if(forward):
try:
analysis_name = "analyse_models";
models = [["resnet18", True, True], ["resnet34", False, True]];
percent_data=40;
analysis = ptf.Analyse_Models(analysis_name, models, percent_data, num_epochs=epochs, state="keep_none");
system_dict["successful_tests"] += 1;
print_status("Pass");
except Exception as e:
system_dict["failed_tests_exceptions"].append(e);
system_dict["failed_tests_lists"].append(test);
forward = False;
print_status("Fail");
else:
system_dict["skipped_tests_lists"].append(test);
print_status("Skipped");
test = "analyse_Analyse_Optimizers()";
system_dict["total_tests"] += 1;
print_start(test, system_dict["total_tests"])
if(forward):
try:
analysis_name = "analyse_optimizers";
optimizers = ["sgd", "adam"];
epochs = 2;
percent_data = 40;
analysis = ptf.Analyse_Optimizers(analysis_name, optimizers, percent_data, num_epochs=epochs, state="keep_none");
system_dict["successful_tests"] += 1;
print_status("Pass");
except Exception as e:
system_dict["failed_tests_exceptions"].append(e);
system_dict["failed_tests_lists"].append(test);
forward = False;
print_status("Fail");
else:
system_dict["skipped_tests_lists"].append(test);
print_status("Skipped");
return system_dict
def test_default_eval_infer(system_dict):
forward = True
if (not os.path.isdir("datasets")):
os.system(
"! wget --load-cookies /tmp/cookies.txt \"https://docs.google.com/uc?export=download&confirm=$(wget --save-cookies /tmp/cookies.txt --keep-session-cookies --no-check-certificate 'https://docs.google.com/uc?export=download&id=1rG-U1mS8hDU7_wM56a1kc-li_zHLtbq2' -O- | sed -rn 's/.*confirm=([0-9A-Za-z_]+).*/\1\n/p')&id=1rG-U1mS8hDU7_wM56a1kc-li_zHLtbq2\" -O datasets.zip && rm -rf /tmp/cookies.txt"
)
os.system("! unzip -qq datasets.zip")
test = "default_eval_infer_object_creation"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf = prototype(verbose=0)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "default_eval_infer_Prototype()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Prototype("sample-project-1",
"sample-experiment-1",
eval_infer=True)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "default_eval_infer_Infer-img()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
img_name = "datasets/dataset_cats_dogs_test/0.jpg"
predictions = ptf.Infer(img_name=img_name, return_raw=True)
img_name = "datasets/dataset_cats_dogs_test/84.jpg"
predictions = ptf.Infer(img_name=img_name, return_raw=True)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "default_eval_infer_Infer-folder()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
inference_dataset = "datasets/dataset_cats_dogs_test"
output = ptf.Infer(img_dir=inference_dataset, return_raw=True)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "default_eval_infer_Dataset_Params()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Dataset_Params(dataset_path="datasets/dataset_cats_dogs_eval")
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "default_eval_infer_Dataset()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Dataset()
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "default_eval_infer_Evaluate()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
accuracy, class_based_accuracy = ptf.Evaluate()
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
return system_dict
def test_update_eval_infer(system_dict):
forward = True
if (not os.path.isdir("datasets")):
os.system(
"! wget --load-cookies /tmp/cookies.txt \"https://docs.google.com/uc?export=download&confirm=$(wget --save-cookies /tmp/cookies.txt --keep-session-cookies --no-check-certificate 'https://docs.google.com/uc?export=download&id=1rG-U1mS8hDU7_wM56a1kc-li_zHLtbq2' -O- | sed -rn 's/.*confirm=([0-9A-Za-z_]+).*/\1\n/p')&id=1rG-U1mS8hDU7_wM56a1kc-li_zHLtbq2\" -O datasets.zip && rm -rf /tmp/cookies.txt"
)
os.system("! unzip -qq datasets.zip")
test = "update_normal_object_creation"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf = prototype(verbose=0)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_normal_Prototype()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Prototype("sample-project-1",
"sample-experiment-3",
eval_infer=True)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_normal_Dataset_Params()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Dataset_Params(dataset_path="datasets/dataset_csv_id/test",
path_to_csv="datasets/dataset_csv_id/test.csv",
delimiter=",")
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "default_eval_infer_Dataset()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Dataset()
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_normal_update_model_path()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.update_model_path(
"workspace/sample-project-1/sample-experiment-3/output/models/best_model"
)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_normal_Reload()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Reload()
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "default_eval_infer_Evaluate()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
accuracy, class_based_accuracy = ptf.Evaluate()
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
return system_dict
def test_switch_default(system_dict):
forward = True
if (not os.path.isdir("datasets")):
os.system(
"! wget --load-cookies /tmp/cookies.txt \"https://docs.google.com/uc?export=download&confirm=$(wget --save-cookies /tmp/cookies.txt --keep-session-cookies --no-check-certificate 'https://docs.google.com/uc?export=download&id=1rG-U1mS8hDU7_wM56a1kc-li_zHLtbq2' -O- | sed -rn 's/.*confirm=([0-9A-Za-z_]+).*/\1\n/p')&id=1rG-U1mS8hDU7_wM56a1kc-li_zHLtbq2\" -O datasets.zip && rm -rf /tmp/cookies.txt"
)
os.system("! unzip -qq datasets.zip")
test = "switch_default_object_object_creation"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf = prototype(verbose=0)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "switch_default_object_Prototype()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Prototype("sample-project-1", "sample-experiment-5")
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "switch_default_Default()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Default(dataset_path=[
"datasets/dataset_cats_dogs_train",
"datasets/dataset_cats_dogs_eval"
],
model_name="resnet18",
freeze_base_network=True,
num_epochs=10)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "switch_default_EDA()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.EDA(check_missing=True, check_corrupt=True)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "switch_default_Switch_Mode()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Switch_Mode(eval_infer=True)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "switch_default_Dataset_Params()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Dataset_Params(dataset_path="datasets/dataset_cats_dogs_eval")
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "switch_default_Dataset()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Dataset()
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "switch_default_Evaluate()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
accuracy, class_based_accuracy = ptf.Evaluate()
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "switch_default_Switch_Mode()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Switch_Mode(train=True)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "switch_default_Train()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Train()
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
return system_dict
def test_switch_expert(system_dict):
forward = True
if (not os.path.isdir("datasets")):
os.system(
"! wget --load-cookies /tmp/cookies.txt \"https://docs.google.com/uc?export=download&confirm=$(wget --save-cookies /tmp/cookies.txt --keep-session-cookies --no-check-certificate 'https://docs.google.com/uc?export=download&id=1rG-U1mS8hDU7_wM56a1kc-li_zHLtbq2' -O- | sed -rn 's/.*confirm=([0-9A-Za-z_]+).*/\1\n/p')&id=1rG-U1mS8hDU7_wM56a1kc-li_zHLtbq2\" -O datasets.zip && rm -rf /tmp/cookies.txt"
)
os.system("! unzip -qq datasets.zip")
test = "switch_expert_object_creation"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf = prototype(verbose=0)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "switch_expert_Prototype()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Prototype("sample-project-1", "sample-experiment-6")
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "switch_expert_switch_mode()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Switch_Mode(eval_infer=True)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "switch_expert_Model_Params()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Model_Params(
model_path=
"workspace/sample-project-1/sample-experiment-5/output/models/intermediate_model_9",
use_gpu=True)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "switch_expert_Model()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Model()
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "switch_expert_update_input_size()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.update_input_size(224)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "switch_expert_Infer-Img()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
img_name = "datasets/dataset_cats_dogs_test/0.jpg"
predictions = ptf.Infer(img_name=img_name, return_raw=True)
img_name = "datasets/dataset_cats_dogs_test/84.jpg"
predictions = ptf.Infer(img_name=img_name, return_raw=True)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "switch_expert_Infer-Folder()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
inference_dataset = "datasets/dataset_cats_dogs_test/"
output = ptf.Infer(img_dir=inference_dataset, return_raw=True)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "switch_expert_Dataset_Params()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Dataset_Params(dataset_path="datasets/dataset_cats_dogs_eval",
input_size=224)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "switch_expert_Dataset()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Dataset()
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "switch_expert_Evaluate()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
accuracy, class_based_accuracy = ptf.Evaluate()
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "switch_expert_switch_mode()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Switch_Mode(train=True)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "expert_train_Dataset_Params()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Dataset_Params(dataset_path="datasets/dataset_cats_dogs_train",
split=0.9,
input_size=224,
batch_size=16,
shuffle_data=True,
num_processors=3)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "expert_train_apply_transforms()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.apply_random_resized_crop(256, train=True, val=True, test=True)
ptf.apply_random_perspective(train=True, val=True)
ptf.apply_random_vertical_flip(train=True, val=True)
ptf.apply_random_horizontal_flip(train=True, val=True)
ptf.apply_normalize(mean=[0.485, 0.456, 0.406],
std=[0.229, 0.224, 0.225],
train=True,
val=True,
test=True)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "expert_train_Dataset()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Dataset()
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "expert_train_Model_Params()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Model_Params(model_name="resnet18",
freeze_base_network=True,
use_gpu=True,
use_pretrained=True)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "expert_train_Model()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Model()
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "expert_train_lr_multistep_decrease()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.lr_multistep_decrease([1, 3], gamma=0.9)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "expert_train_optimizer_sgd()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.optimizer_sgd(0.001, momentum=0.9)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "expert_train_loss_softmax_crossentropy()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.loss_softmax_crossentropy()
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "expert_train_Training_Params()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Training_Params(
num_epochs=4,
display_progress=True,
display_progress_realtime=True,
save_intermediate_models=True,
intermediate_model_prefix="intermediate_model_",
save_training_logs=True)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "expert_train_Train()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Train()
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
return system_dict
def test_expert_train(system_dict):
forward = True
if (not os.path.isdir("datasets")):
os.system(
"! wget --load-cookies /tmp/cookies.txt \"https://docs.google.com/uc?export=download&confirm=$(wget --save-cookies /tmp/cookies.txt --keep-session-cookies --no-check-certificate 'https://docs.google.com/uc?export=download&id=1rG-U1mS8hDU7_wM56a1kc-li_zHLtbq2' -O- | sed -rn 's/.*confirm=([0-9A-Za-z_]+).*/\1\n/p')&id=1rG-U1mS8hDU7_wM56a1kc-li_zHLtbq2\" -O datasets.zip && rm -rf /tmp/cookies.txt"
)
os.system("! unzip -qq datasets.zip")
test = "expert_train_object_creation"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf = prototype(verbose=0)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "expert_train_Prototype()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Prototype("sample-project-1", "sample-experiment-4")
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "expert_train_Dataset_Params()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Dataset_Params(dataset_path=[
"datasets/dataset_csv_id/train", "datasets/dataset_csv_id/val"
],
path_to_csv=[
"datasets/dataset_csv_id/train.csv",
"datasets/dataset_csv_id/val.csv"
],
split=0.9,
input_size=224,
batch_size=16,
shuffle_data=True,
num_processors=3)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "expert_train_Dataset()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Dataset()
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "expert_train_Model_Params()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Model_Params(model_name="resnet18",
freeze_base_network=True,
use_gpu=True,
use_pretrained=True)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "expert_train_append_layer()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.append_dropout(probability=0.1)
ptf.append_linear(final_layer=True)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "expert_train_Model()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Model()
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "expert_train_lr_step_decrease()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.lr_step_decrease(1, gamma=0.9)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "expert_train_optimizer_sgd()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.optimizer_sgd(0.001, momentum=0.9)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "expert_train_loss_softmax_crossentropy()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.loss_softmax_crossentropy()
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "expert_train_Training_Params()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Training_Params(
num_epochs=3,
display_progress=True,
display_progress_realtime=True,
save_intermediate_models=True,
intermediate_model_prefix="intermediate_model_",
save_training_logs=True)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "expert_train_Train()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Train()
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
return system_dict
def test_layer_concatenate(system_dict):
forward = True
test = "test_layer_concatenate"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
gtf = prototype(verbose=0)
gtf.Prototype("sample-project-1", "sample-experiment-1")
network = []
network.append(gtf.convolution(output_channels=16))
network.append(gtf.batch_normalization())
network.append(gtf.relu())
network.append(gtf.max_pooling())
subnetwork = []
branch1 = []
branch1.append(gtf.convolution(output_channels=16))
branch1.append(gtf.batch_normalization())
branch1.append(gtf.convolution(output_channels=16))
branch1.append(gtf.batch_normalization())
branch2 = []
branch2.append(gtf.convolution(output_channels=16))
branch2.append(gtf.batch_normalization())
branch3 = []
branch3.append(gtf.identity())
subnetwork.append(branch1)
subnetwork.append(branch2)
subnetwork.append(branch3)
subnetwork.append(gtf.concatenate())
network.append(subnetwork)
network.append(gtf.convolution(output_channels=16))
network.append(gtf.batch_normalization())
network.append(gtf.relu())
network.append(gtf.max_pooling())
network.append(gtf.flatten())
network.append(gtf.fully_connected(units=1024))
network.append(gtf.dropout(drop_probability=0.2))
network.append(gtf.fully_connected(units=2))
gtf.Compile_Network(network, data_shape=(3, 64, 64), use_gpu=False)
x = torch.randn(1, 3, 64, 64)
y = gtf.system_dict["local"]["model"](x)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
return system_dict
def test_update_copy_from(system_dict):
forward = True
if (not os.path.isdir("datasets")):
os.system(
"! wget --load-cookies /tmp/cookies.txt \"https://docs.google.com/uc?export=download&confirm=$(wget --save-cookies /tmp/cookies.txt --keep-session-cookies --no-check-certificate 'https://docs.google.com/uc?export=download&id=1rG-U1mS8hDU7_wM56a1kc-li_zHLtbq2' -O- | sed -rn 's/.*confirm=([0-9A-Za-z_]+).*/\1\n/p')&id=1rG-U1mS8hDU7_wM56a1kc-li_zHLtbq2\" -O datasets.zip && rm -rf /tmp/cookies.txt"
)
os.system("! unzip -qq datasets.zip")
test = "update_copy_from_object_creation"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf = prototype(verbose=0)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_copy_from_Prototype()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Prototype(
"sample-project-1",
"sample-experiment-2",
copy_from=["sample-project-1", "sample-experiment-1"])
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_copy_from_reset_transforms()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.reset_transforms()
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_copy_from_apply_transforms()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.apply_random_resized_crop(256, train=True, val=True, test=True)
ptf.apply_random_perspective(train=True, val=True)
ptf.apply_random_vertical_flip(train=True, val=True)
ptf.apply_random_horizontal_flip(train=True, val=True)
ptf.apply_normalize(mean=[0.485, 0.456, 0.406],
std=[0.229, 0.224, 0.225],
train=True,
val=True,
test=True)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_copy_from_update_dataset()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.update_dataset(dataset_path=[
"datasets/dataset_cats_dogs_train",
"datasets/dataset_cats_dogs_eval"
])
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_copy_from_update_input_size()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.update_input_size(256)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_copy_from_update_batch_size()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.update_batch_size(6)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_copy_from_update_shuffle_data()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.update_shuffle_data(False)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_copy_from_update_num_processors()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.update_num_processors(16)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_copy_from_update_trainval_split()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.update_trainval_split(0.6)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_copy_from_Reload()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Reload()
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_copy_from_EDA()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.EDA(check_missing=True, check_corrupt=True)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_copy_from_Train()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Train()
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
return system_dict
def test_update_normal(system_dict):
forward = True
if (not os.path.isdir("datasets")):
os.system(
"! wget --load-cookies /tmp/cookies.txt \"https://docs.google.com/uc?export=download&confirm=$(wget --save-cookies /tmp/cookies.txt --keep-session-cookies --no-check-certificate 'https://docs.google.com/uc?export=download&id=1rG-U1mS8hDU7_wM56a1kc-li_zHLtbq2' -O- | sed -rn 's/.*confirm=([0-9A-Za-z_]+).*/\1\n/p')&id=1rG-U1mS8hDU7_wM56a1kc-li_zHLtbq2\" -O datasets.zip && rm -rf /tmp/cookies.txt"
)
os.system("! unzip -qq datasets.zip")
test = "update_normal_object_creation"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf = prototype(verbose=0)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_normal_Prototype()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Prototype("sample-project-1", "sample-experiment-3")
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_normal_Default()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Default(dataset_path="datasets/dataset_csv_id/train",
path_to_csv="datasets/dataset_csv_id/train.csv",
delimiter=",",
model_name="resnet18",
freeze_base_network=True,
num_epochs=10)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_normal_update_model_name()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.update_model_name("resnet50")
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_normal_update_use_gpu()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.update_use_gpu(False)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_normal_update_use_pretrained()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.update_use_pretrained(True)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_normal_update_freeze_base_network()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.update_freeze_base_network(False)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_normal_update_freeze_layers()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.update_freeze_layers(10)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_normal_update_num_epochs()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.update_num_epochs(2)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_normal_update_display_progress_realtime()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.update_display_progress_realtime(False)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_normal_update_display_progress()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.update_display_progress(False)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_normal_update_save_intermediate_models()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.update_save_intermediate_models(False)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_normal_update_save_training_logs()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.update_save_training_logs(True)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_normal_lr_fixed()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.lr_fixed()
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_normal_Reload()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Reload()
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_normal_EDA()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.EDA(check_missing=True, check_corrupt=True)
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_normal_Estimate_Train_Time()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Estimate_Train_Time()
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
test = "update_normal_Train()"
system_dict["total_tests"] += 1
print_start(test, system_dict["total_tests"])
if (forward):
try:
ptf.Train()
system_dict["successful_tests"] += 1
print_status("Pass")
except Exception as e:
system_dict["failed_tests_exceptions"].append(e)
system_dict["failed_tests_lists"].append(test)
forward = False
print_status("Fail")
else:
system_dict["skipped_tests_lists"].append(test)
print_status("Skipped")
return system_dict
