diff options
Diffstat (limited to 'tensorflow/contrib/fused_conv/python/ops/fused_conv2d_bias_activation_op_test.py')
| -rw-r--r-- | tensorflow/contrib/fused_conv/python/ops/fused_conv2d_bias_activation_op_test.py | 25 |
1 files changed, 16 insertions, 9 deletions
diff --git a/tensorflow/contrib/fused_conv/python/ops/fused_conv2d_bias_activation_op_test.py b/tensorflow/contrib/fused_conv/python/ops/fused_conv2d_bias_activation_op_test.py index 4d62ac65ff..0185ef662c 100644 --- a/tensorflow/contrib/fused_conv/python/ops/fused_conv2d_bias_activation_op_test.py +++ b/tensorflow/contrib/fused_conv/python/ops/fused_conv2d_bias_activation_op_test.py @@ -622,7 +622,7 @@ def HwioToOihw(in_tensor): def SimulateFusedConv2dBiasActivationInt8(conv_input_scale, conv_input, kernel, padding, strides, side_input_scale, - side_input, biases): + side_input, biases, apply_relu): """Simulates the int8 fused 2-D convolution op using separate float ops. The arguments and return values have the same format, meanings and @@ -636,6 +636,9 @@ def SimulateFusedConv2dBiasActivationInt8(conv_input_scale, conv_input, kernel, side_input_scale: A scalar 'float'. side_input: A `Tensor` of type `qint8` in NCHW_VECT_C layout. biases: A `Tensor` of type `float32` in NCHW layout. + apply_relu: A boolean to specify whether to apply "Relu" activation function + that clips outputs to the range [0, 127], or "None" activation that clips + to the range [-128, 127]. Returns: A `Tensor` of type `qint8` in NCHW_VECT_C layout. """ @@ -649,10 +652,12 @@ def SimulateFusedConv2dBiasActivationInt8(conv_input_scale, conv_input, kernel, conv_and_side_inputs = conv_result + side_input_scale * NchwVectCToNchw( gen_array_ops.dequantize(side_input, -128, 127)) - logit = nn_ops.bias_add(conv_and_side_inputs, biases, data_format="NCHW") + output = nn_ops.bias_add(conv_and_side_inputs, biases, data_format="NCHW") + if apply_relu: + output = nn_ops.relu(output) result, _, _ = gen_array_ops.quantize_v2( - NchwToNchwVectC(nn_ops.relu(logit)), -128, 127, dtypes.qint8) + NchwToNchwVectC(output), -128, 127, dtypes.qint8) return result @@ -795,7 +800,7 @@ class FusedConvInt8Tests(test.TestCase): }, ] - def runTest(self, test_param): + def runTest(self, test_param, apply_relu): batch_size = test_param["batch_size"] input_channels = test_param["input_channels"] output_channels = test_param["output_channels"] @@ -831,8 +836,8 @@ class FusedConvInt8Tests(test.TestCase): vertical_stride, padding_type) output_width = CalculateConvolvedOutputDim(input_width, filter_width, horizontal_stride, padding_type) - tf_logging.info("output_height=", output_height, ", output_width=", - output_width) + tf_logging.info("output_height=", output_height, ", output_width=", + output_width) side_input, _, _ = gen_array_ops.quantize_v2( random_ops.random_uniform( @@ -858,12 +863,13 @@ class FusedConvInt8Tests(test.TestCase): conv_input_scale=conv_input_scale, side_input_scale=side_input_scale, side_input=side_input, + activation_mode="Relu" if apply_relu else "None", data_format="NCHW_VECT_C", filter_format="OIHW_VECT_I") expected = SimulateFusedConv2dBiasActivationInt8( conv_input_scale, conv_input, kernel, padding_type, strides, - side_input_scale, side_input, biases) + side_input_scale, side_input, biases, apply_relu) with self.test_session(use_gpu=True) as sess: actual_y, expected_y = sess.run([actual, expected]) @@ -877,8 +883,9 @@ class FusedConvInt8Tests(test.TestCase): tf_logging.info("int8 test skipped because not run with --config=cuda or " "no GPUs with compute capability >= 6.1 are available.") return - for test_param in self._test_params: - self.runTest(test_param) + for apply_relu in [True, False]: + for test_param in self._test_params: + self.runTest(test_param, apply_relu) if __name__ == "__main__": |