diff options
author | ImSheridan <xiaoyudong0512@gmail.com> | 2018-06-04 12:50:12 +0800 |
---|---|---|
committer | Gunhan Gulsoy <gunan@google.com> | 2018-06-03 21:50:12 -0700 |
commit | 63dafb7f5dbef4da63e095595a49f5d5d7258af9 (patch) | |
tree | 4541b20582d87587029b8fb536e3badd8b3ee63b | |
parent | 320d8056af7799ab20e339757cf379963148425a (diff) |
Fix print function with tf_logging.info to keep consistence (#18423)
* Fix print function with tf_logging.info to keep consistence
* fix minor typo
* fix pylint errors
* Fix minor pylint errors
* Fix lint error
5 files changed, 32 insertions, 31 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 3d0ed89932..4d62ac65ff 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 @@ -289,8 +289,8 @@ class FusedConv2DBiasActivationTest(test.TestCase): conv = tensors[i] value = values[i] ref_value = ref_values[i] - print("expected = ", ref_value) - print("actual = ", value) + tf_logging.info("expected = ", ref_value) + tf_logging.info("actual = ", value) tol = 1e-5 if value.dtype == np.float16: tol = 1e-3 @@ -831,7 +831,8 @@ class FusedConvInt8Tests(test.TestCase): vertical_stride, padding_type) output_width = CalculateConvolvedOutputDim(input_width, filter_width, horizontal_stride, padding_type) - print("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( @@ -866,8 +867,8 @@ class FusedConvInt8Tests(test.TestCase): with self.test_session(use_gpu=True) as sess: actual_y, expected_y = sess.run([actual, expected]) - print("actual_y = ", actual_y) - print("expected_y = ", expected_y) + tf_logging.info("actual_y = ", actual_y) + tf_logging.info("expected_y = ", expected_y) self.assertTrue(np.array_equal(actual_y, expected_y)) def testFusedConvInt8(self): diff --git a/tensorflow/python/kernel_tests/betainc_op_test.py b/tensorflow/python/kernel_tests/betainc_op_test.py index 08b03f8518..16fdedac41 100644 --- a/tensorflow/python/kernel_tests/betainc_op_test.py +++ b/tensorflow/python/kernel_tests/betainc_op_test.py @@ -172,7 +172,7 @@ class BetaincTest(test.TestCase): tf_gout_t = math_ops.betainc(tf_ga_s, tf_gb_s, tf_gx_s) err = gradient_checker.compute_gradient_error( [tf_gx_s], [gx_s.shape], tf_gout_t, gx_s.shape) - print("betainc gradient err = %g " % err) + tf_logging.info("betainc gradient err = %g " % err) self.assertLess(err, err_tolerance) # Test broadcast gradient @@ -181,7 +181,7 @@ class BetaincTest(test.TestCase): tf_gout_t = math_ops.betainc(tf_ga_s, tf_gb_s, tf_gx_s) err = gradient_checker.compute_gradient_error( [tf_gx_s], [()], tf_gout_t, ga_s.shape) - print("betainc gradient err = %g " % err) + tf_logging.info("betainc gradient err = %g " % err) self.assertLess(err, err_tolerance) diff --git a/tensorflow/python/kernel_tests/conv_ops_test.py b/tensorflow/python/kernel_tests/conv_ops_test.py index a291bef0ad..450428707d 100644 --- a/tensorflow/python/kernel_tests/conv_ops_test.py +++ b/tensorflow/python/kernel_tests/conv_ops_test.py @@ -312,8 +312,8 @@ class Conv2DTest(test.TestCase): expected_values = self.evaluate(expected_results) computed_values = self.evaluate(computed_results) for e_value, c_value in zip(expected_values, computed_values): - print("expected = ", e_value) - print("actual = ", c_value) + tf_logging.info("expected = ", e_value) + tf_logging.info("actual = ", c_value) self.assertAllClose( e_value.flatten(), c_value.flatten(), atol=tolerance, rtol=1e-4) @@ -337,8 +337,8 @@ class Conv2DTest(test.TestCase): for i in range(len(tensors)): conv = tensors[i] value = values[i] - print("expected = ", expected) - print("actual = ", value) + tf_logging.info("expected = ", expected) + tf_logging.info("actual = ", value) tol = 1e-5 if value.dtype == np.float16: tol = 1e-3 @@ -547,8 +547,8 @@ class Conv2DTest(test.TestCase): # "values" consists of two tensors for two backprops value = self.evaluate(conv) self.assertShapeEqual(value, conv) - print("expected = ", expected) - print("actual = ", value) + tf_logging.info("expected = ", expected) + tf_logging.info("actual = ", value) self.assertArrayNear(expected, value.flatten(), err) def _CompareBackpropInput(self, input_sizes, filter_sizes, output_sizes, @@ -723,8 +723,8 @@ class Conv2DTest(test.TestCase): data_format=data_format) value = self.evaluate(conv) self.assertShapeEqual(value, conv) - print("expected = ", expected) - print("actual = ", value) + tf_logging.info("expected = ", expected) + tf_logging.info("actual = ", value) self.assertArrayNear(expected, value.flatten(), 1e-5) def _CompareBackFilter(self, input_sizes, filter_sizes, output_sizes, @@ -912,8 +912,8 @@ class Conv2DTest(test.TestCase): value_2 = sess.run(conv_2) self.assertShapeEqual(value, conv) self.assertShapeEqual(value_2, conv_2) - print("expected = ", value_2) - print("actual = ", value) + tf_logging.info("expected = ", value_2) + tf_logging.info("actual = ", value) self.assertArrayNear(value_2.flatten(), value.flatten(), err) # Testing for backprops @@ -965,8 +965,8 @@ class Conv2DTest(test.TestCase): value_2 = sess.run(conv_2) self.assertShapeEqual(value, conv) self.assertShapeEqual(value_2, conv_2) - print("expected = ", value_2) - print("actual = ", value) + tf_logging.info("expected = ", value_2) + tf_logging.info("actual = ", value) self.assertArrayNear(value_2.flatten(), value.flatten(), err) def testConv2D2x2Depth3ValidBackpropFilterStride1x1Dilation2x1(self): @@ -1178,7 +1178,7 @@ class Conv2DTest(test.TestCase): # since fp16 numerical gradients are too imprecise. err = np.fabs(jacob_t - reference_jacob_t).max() - print("conv_2d gradient error = ", err) + tf_logging.info("conv_2d gradient error = ", err) self.assertLess(err, 0.002) def testInputGradientValidPaddingStrideOne(self): @@ -1546,7 +1546,7 @@ class DepthwiseConv2DTest(test.TestCase): conv = nn_impl.depthwise_conv2d( t1, t2, strides=[1, stride, stride, 1], padding=padding) value = sess.run(conv) - print("value = ", value) + tf_logging.info("value = ", value) self.assertArrayNear(expected, np.ravel(value), 1e-5) self.assertShapeEqual(value, conv) @@ -1668,7 +1668,7 @@ class SeparableConv2DTest(test.TestCase): conv = array_ops.transpose(conv, [0, 2, 3, 1]) value = sess.run(conv) - print("value = ", value) + tf_logging.info("value = ", value) self.assertArrayNear(expected, np.ravel(value), 1e-5) self.assertShapeEqual(value, conv) @@ -1826,7 +1826,7 @@ class Conv2DBenchmark(test.Benchmark): wall_time = time.time() - start self.report_benchmark( name="conv_stack_iter_%d" % iter_index, wall_time=wall_time) - print("conv_stack_iter_%d: %.4f" % (iter_index, wall_time)) + tf_logging.info("conv_stack_iter_%d: %.4f" % (iter_index, wall_time)) def GetInceptionFwdTest(input_size, filter_size, stride, padding, diff --git a/tensorflow/python/kernel_tests/pooling_ops_test.py b/tensorflow/python/kernel_tests/pooling_ops_test.py index a0c372db7d..e95c729715 100644 --- a/tensorflow/python/kernel_tests/pooling_ops_test.py +++ b/tensorflow/python/kernel_tests/pooling_ops_test.py @@ -947,7 +947,7 @@ class PoolingTest(test.TestCase): output_sizes, x_init_value=x_init_value, delta=1e-2) - print("%s gradient error = " % func_name, err) + tf_logging.info("%s gradient error = " % func_name, err) self.assertLess(err, err_tolerance) def _ConstructAndTestSecondGradient(self, @@ -1024,7 +1024,7 @@ class PoolingTest(test.TestCase): input_sizes, x_init_value=x_init_value, delta=1e-2) - print("%s second-order gradient error = " % func_name, err) + tf_logging.info("%s second-order gradient error = " % func_name, err) self.assertLess(err, err_tolerance) def _testMaxPoolGradValidPadding1_1(self, data_format, use_gpu): diff --git a/tensorflow/tools/quantization/quantize_graph_test.py b/tensorflow/tools/quantization/quantize_graph_test.py index df71840b64..92bb5127da 100644 --- a/tensorflow/tools/quantization/quantize_graph_test.py +++ b/tensorflow/tools/quantization/quantize_graph_test.py @@ -119,8 +119,8 @@ def are_tensors_near(a, b, tolerance): flat_a = a.flatten() flat_b = b.flatten() if len(flat_a) != len(flat_b): - print("Tensors are different sizes: " + str(len(flat_a)) + " vs " + str( - len(flat_b))) + tf_logging.info("Tensors are different sizes: " + str(len(flat_a)) + " vs " + + str(len(flat_b))) return False value_count = len(flat_a) how_many_different = 0 @@ -140,10 +140,10 @@ def are_tensors_near(a, b, tolerance): if how_many_different == 0: return True else: - print("Tensors have {0} different values ({1}%), with mean difference" - " {2} and mean absolute difference {3}".format( - how_many_different, proportion_different * 100, mean_difference, - mean_abs_difference)) + tf_logging.info("Tensors have {0} different values ({1}%), with mean" + " difference {2} and mean absolute difference {3}".format( + how_many_different, proportion_different * 100, + mean_difference, mean_abs_difference)) return False |