def test_extract(self, T, n, d):
model = ModelHelper(name='external')
workspace.ResetWorkspace()
input_blob, initial_input_blob = model.net.AddExternalInputs(
'input', 'initial_input')
step = ModelHelper(name='step', param_model=model)
input_t, output_t_prev = step.net.AddExternalInput(
'input_t', 'output_t_prev')
output_t = step.net.Mul([input_t, output_t_prev])
step.net.AddExternalOutput(output_t)
inputs = np.random.randn(T, n, d).astype(np.float32)
initial_input = np.random.randn(1, n, d).astype(np.float32)
recurrent.recurrent_net(
net=model.net,
cell_net=step.net,
inputs=[(input_t, input_blob)],
initial_cell_inputs=[(output_t_prev, initial_input_blob)],
links={output_t_prev: output_t},
scope="test_rnn_sum_mull",
)
workspace.blobs[input_blob] = inputs
workspace.blobs[initial_input_blob] = initial_input
workspace.RunNetOnce(model.param_init_net)
workspace.CreateNet(model.net)
prefix = "extractTest"
workspace.RunNet(model.net.Proto().name, T)
retrieved_blobs = recurrent.retrieve_step_blobs(
model.net, prefix
)
# needed for python3.6, which returns bytearrays instead of str
retrieved_blobs = [x.decode() for x in retrieved_blobs]
for i in range(T):
blob_name = prefix + "_" + "input_t" + str(i)
self.assertTrue(
blob_name in retrieved_blobs,
"blob extraction failed on timestep {}\
. \n\n Extracted Blobs: {} \n\n Looking for {}\
.".format(i, retrieved_blobs, blob_name)
)
def test_extract(self, T, n, d):
model = ModelHelper(name='external')
workspace.ResetWorkspace()
input_blob, initial_input_blob = model.net.AddExternalInputs(
'input', 'initial_input')
step = ModelHelper(name='step', param_model=model)
input_t, output_t_prev = step.net.AddExternalInput(
'input_t', 'output_t_prev')
output_t = step.net.Mul([input_t, output_t_prev])
step.net.AddExternalOutput(output_t)
inputs = np.random.randn(T, n, d).astype(np.float32)
initial_input = np.random.randn(1, n, d).astype(np.float32)
recurrent.recurrent_net(
net=model.net,
cell_net=step.net,
inputs=[(input_t, input_blob)],
initial_cell_inputs=[(output_t_prev, initial_input_blob)],
links={output_t_prev: output_t},
scope="test_rnn_sum_mull",
)
workspace.blobs[input_blob] = inputs
workspace.blobs[initial_input_blob] = initial_input
workspace.RunNetOnce(model.param_init_net)
workspace.CreateNet(model.net)
prefix = "extractTest"
workspace.RunNet(model.net.Proto().name, T)
retrieved_blobs = recurrent.retrieve_step_blobs(
model.net, prefix
)
# needed for python3.6, which returns bytearrays instead of str
retrieved_blobs = [x.decode() for x in retrieved_blobs]
for i in range(T):
blob_name = prefix + "_" + "input_t" + str(i)
self.assertTrue(
blob_name in retrieved_blobs,
"blob extraction failed on timestep {}\
. \n\n Extracted Blobs: {} \n\n Looking for {}\
.".format(i, retrieved_blobs, blob_name)
)
