def test_group_convolution_operator():
runtime = get_runtime()
data_shape = [1, 4, 2, 2]
filters_shape = [2, 1, 2, 1, 1]
parameter_data = ng.parameter(data_shape, name="Data", dtype=np.float32)
parameter_filters = ng.parameter(filters_shape,
name="Filters",
dtype=np.float32)
data_value = np.arange(start=1.0, stop=17.0,
dtype=np.float32).reshape(data_shape)
filters_value = np.arange(start=1.0, stop=5.0,
dtype=np.float32).reshape(filters_shape)
strides = [1, 1]
dilations = [1, 1]
pads_begin = [0, 0]
pads_end = [0, 0]
model = ng.group_convolution(parameter_data, parameter_filters, strides,
pads_begin, pads_end, dilations)
computation = runtime.computation(model, parameter_data, parameter_filters)
result = computation(data_value, filters_value)
expected = np.array([11, 14, 17, 20, 79, 86, 93, 100],
dtype=np.float32).reshape(1, 2, 2, 2)
assert np.allclose(result, expected)
def test_group_convolution_operator():
runtime = get_runtime()
data_shape = [1, 4, 2, 2]
filters_shape = [2, 2, 1, 1]
parameter_data = ng.parameter(data_shape, name='Data', dtype=np.float32)
parameter_filters = ng.parameter(filters_shape, name='Filters', dtype=np.float32)
data_value = np.arange(start=1.0, stop=17.0, dtype=np.float32).reshape(data_shape)
filters_value = np.arange(start=1.0, stop=5.0, dtype=np.float32).reshape(filters_shape)
window_movement_strides = [1, 1]
window_dilation_strides = [1, 1]
padding_below = [0, 0]
padding_above = [0, 0]
data_dilation_strides = [1, 1]
groups = 2
model = ng.group_convolution(parameter_data,
parameter_filters,
window_movement_strides,
window_dilation_strides,
padding_below, padding_above,
data_dilation_strides,
groups,
0)
computation = runtime.computation(model, parameter_data, parameter_filters)
result = computation(data_value, filters_value)
expected = np.array([11, 14, 17, 20, 79, 86, 93, 100],
dtype=np.float32).reshape(1, 2, 2, 2)
assert np.allclose(result, expected)
