def test_invalid_parameters(in_dtype, out_dtype, zero_point, scale,
out_zero_point, out_scale):
model = make_model([1, 16, 16, 3], in_dtype, out_dtype, zero_point, scale,
out_zero_point, out_scale)
orig_mod = make_module(model)
cmsisnn_mod = cmsisnn.partition_for_cmsisnn(orig_mod)
assert_no_external_function(cmsisnn_mod)
def test_invalid_batch_size(op):
model = make_model(
pool_op=op,
shape=(2, 28, 28, 12),
)
orig_mod = make_module(model)
cmsisnn_mod = cmsisnn.partition_for_cmsisnn(orig_mod)
assert_no_external_function(cmsisnn_mod)
def test_invalid_parameters(
in_dtype,
kernel_dtype,
kernel_zero_point,
):
ifm_shape = (1, 28, 28, 12)
out_channels = 2
input_scale = 1
input_zero_point = 24
kernel_scale = [0.11, 0.0237]
in_min, in_max = get_range_for_dtype_str(in_dtype)
kernel_layout = "HWIO"
kernel_shape = [3, 3, ifm_shape[3], out_channels]
output_scale, output_zero_point = get_conv2d_qnn_params(
kernel_shape,
input_scale,
input_zero_point,
kernel_scale,
kernel_zero_point,
in_dtype,
kernel_dtype,
in_dtype,
False,
)
model, params = make_model(
shape=ifm_shape,
kernel_shape=kernel_shape,
input_zero_point=input_zero_point,
input_scale=input_scale,
kernel_zero_point=kernel_zero_point,
kernel_scale=kernel_scale,
output_zero_point=output_zero_point,
output_scale=output_scale,
padding="SAME",
strides=(1, 1),
dilation=(1, 1),
groups=1,
dtype=in_dtype,
kernel_dtype=kernel_dtype,
out_channels=out_channels,
weight_format=kernel_layout,
enable_bias=True,
relu_type="NONE",
)
orig_mod = make_module(model)
cmsisnn_mod = cmsisnn.partition_for_cmsisnn(orig_mod, params)
assert_no_external_function(cmsisnn_mod)
def test_invalid_parameters():
model = make_model(
pool_op=relay.nn.avg_pool2d,
shape=(1, 28, 28, 12),
pool_size=(1, 1),
strides=(1, 1),
padding="VALID",
dtype="uint8",
scale=1,
zero_point=-33,
relu_type="RELU",
)
orig_mod = make_module(model)
cmsisnn_mod = cmsisnn.partition_for_cmsisnn(orig_mod)
assert_no_external_function(cmsisnn_mod)
def test_both_scalar_inputs_int8(op, ):
input_scale = 0.256
input_zero_point = 33
dtype = "int8"
model = make_model(
op,
generate_scalar_constant(),
generate_scalar_constant(),
input_scale,
input_zero_point,
input_scale,
input_zero_point,
)
orig_mod = make_module(model)
cmsisnn_mod = cmsisnn.partition_for_cmsisnn(orig_mod)
assert_no_external_function(cmsisnn_mod)
def test_invalid_parameters(
op,
input_dtype,
):
input_scale = 0.256
input_zero_point = 33
model = make_model(
op,
generate_variable("input_0", input_dtype),
generate_variable("input_1", input_dtype),
input_scale,
input_zero_point,
input_scale,
input_zero_point,
)
orig_mod = make_module(model)
cmsisnn_mod = cmsisnn.partition_for_cmsisnn(orig_mod)
assert_no_external_function(cmsisnn_mod)
def test_invalid_parameters(
in_dtype,
kernel_dtype,
kernel_zero_point,
):
in_shape = (2, 28)
out_channels = 2
input_scale = 1
input_zero_point = 24
kernel_scale = [0.11, 0.0237]
in_min, in_max = get_range_for_dtype_str(in_dtype)
kernel_shape = [out_channels, in_shape[1]]
conv2d_kernel_shape = [1, 1, kernel_shape[0], kernel_shape[1]]
output_scale, output_zero_point = get_conv2d_qnn_params(
conv2d_kernel_shape,
input_scale,
input_zero_point,
kernel_scale,
kernel_zero_point,
in_dtype,
kernel_dtype,
in_dtype,
)
model, params = make_model(
in_shape=in_shape,
kernel_shape=kernel_shape,
input_zero_point=input_zero_point,
kernel_zero_point=kernel_zero_point,
input_scale=input_scale,
kernel_scale=kernel_scale,
output_zero_point=output_zero_point,
output_scale=output_scale,
dtype=in_dtype,
kernel_dtype=kernel_dtype,
out_channels=out_channels,
enable_bias=True,
)
orig_mod = make_module(model)
cmsisnn_mod = cmsisnn.partition_for_cmsisnn(orig_mod, params)
# validate pattern matching
assert_no_external_function(cmsisnn_mod)
def test_invalid_layout(op):
model = make_model(pool_op=op, layout="NCHW")
orig_mod = make_module(model)
cmsisnn_mod = cmsisnn.partition_for_cmsisnn(orig_mod)
assert_no_external_function(cmsisnn_mod)
def test_invalid_datatype(op):
model = make_model(pool_op=op, dtype="int64")
orig_mod = make_module(model)
cmsisnn_mod = cmsisnn.partition_for_cmsisnn(orig_mod)
assert_no_external_function(cmsisnn_mod)
