test_custom_brew_helpers.py 文件源码

def fc_explicit_param_names(self):
        brew.Register(fc_explicit_param_names)
        model = model_helper.ModelHelper(name="test_model")
        dim_in = 10
        dim_out = 100
        weight_name = 'test_weight_name'
        bias_name = 'test_bias_name'
        inputs_name = 'test_inputs'
        output_name = 'test_output'

        input_distribution = stats.norm()
        inputs = input_distribution.rvs(size=(1, dim_in)).astype(np.float32)
        workspace.FeedBlob(inputs_name, inputs)

        weights = np.random.normal(size=(dim_out, dim_in)).astype(np.float32)
        bias = np.transpose(
            np.random.normal(size=(dim_out, )).astype(np.float32)
        )

        brew.fc_explicit_param_names(
            model,
            inputs_name,
            output_name,
            dim_in=dim_in,
            dim_out=dim_out,
            bias_name=bias_name,
            weight_name=weight_name,
            weight_init=("GivenTensorFill", {'values': weights}),
            bias_init=("GivenTensorFill", {'values': bias})
        )

        workspace.RunNetOnce(model.param_init_net)
        workspace.RunNetOnce(model.net)

        expected_output = np.dot(inputs, np.transpose(weights)) + bias
        outputs_diff = expected_output - workspace.FetchBlob(output_name)

        self.assertEqual(np.linalg.norm(outputs_diff), 0)