diff options
Diffstat (limited to 'tensorflow/python/kernel_tests/bias_op_test.py')
| -rw-r--r-- | tensorflow/python/kernel_tests/bias_op_test.py | 16 |
1 files changed, 14 insertions, 2 deletions
diff --git a/tensorflow/python/kernel_tests/bias_op_test.py b/tensorflow/python/kernel_tests/bias_op_test.py index 87027c8a78..862948610d 100644 --- a/tensorflow/python/kernel_tests/bias_op_test.py +++ b/tensorflow/python/kernel_tests/bias_op_test.py @@ -128,7 +128,13 @@ class BiasAddTest(tf.test.TestCase): input_tensor, np_input.shape, output_tensor, np_input.shape) bias_jacob_t, bias_jacob_n = tf.test.compute_gradient( bias_tensor, bias.shape, output_tensor, np_input.shape) - + + # Test gradient of BiasAddGrad + bias_add_grad = tf.gradients(tf.nn.l2_loss(output_tensor), + bias_tensor)[0] + grad_jacob_t, grad_jacob_n = tf.test.compute_gradient( + output_tensor, np_input.shape, bias_add_grad, bias.shape) + if dtype == np.float16: # Compare fp16 theoretical gradients to fp32 numerical gradients, # since fp16 numerical gradients are too imprecise unless great @@ -144,12 +150,18 @@ class BiasAddTest(tf.test.TestCase): input_tensor, np_input.shape, output_tensor, np_input.shape) _, bias_jacob_n = tf.test.compute_gradient( bias_tensor, bias.shape, output_tensor, np_input.shape) - + + bias_add_grad = tf.gradients(tf.nn.l2_loss(output_tensor), + bias_tensor)[0] + _, grad_jacob_n = tf.test.compute_gradient( + output_tensor, np_input.shape, bias_add_grad, bias.shape) + threshold = 2e-3 if dtype == tf.float64: threshold = 1e-10 self.assertAllClose(tensor_jacob_t, tensor_jacob_n, threshold, threshold) self.assertAllClose(bias_jacob_t, bias_jacob_n, threshold, threshold) + self.assertAllClose(grad_jacob_t, grad_jacob_n, threshold, threshold) def testGradientTensor(self): for (data_format, use_gpu) in GetTestConfigs(): |