From 26ef37bef3b04d18698b29f361f10f25f14539cc Mon Sep 17 00:00:00 2001 From: Siju Samuel Date: Fri, 5 Jul 2019 09:53:27 +0530 Subject: [PATCH] deprecated keep_prob removed from dropout in nn_test.py --- tensorflow/python/ops/nn_test.py | 28 ++++++++++++++-------------- 1 file changed, 14 insertions(+), 14 deletions(-) diff --git a/tensorflow/python/ops/nn_test.py b/tensorflow/python/ops/nn_test.py index df07721e5d3..18d0de0b9b6 100644 --- a/tensorflow/python/ops/nn_test.py +++ b/tensorflow/python/ops/nn_test.py @@ -313,7 +313,7 @@ class DropoutTest(test_lib.TestCase): num_iter = 10 for keep_prob in [0.1, 0.5, 0.8]: t = constant_op.constant(1.0, shape=[x_dim, y_dim], dtype=dtypes.float32) - dropout = nn_ops.dropout(t, keep_prob) + dropout = nn_ops.dropout(t, rate=(1 - keep_prob)) final_count = 0 self.assertEqual([x_dim, y_dim], dropout.get_shape()) for _ in xrange(0, num_iter): @@ -340,7 +340,7 @@ class DropoutTest(test_lib.TestCase): num_iter = 10 for keep_prob in [0.1, 0.5, 0.8]: t = constant_op.constant(1.0, shape=[x_dim, y_dim], dtype=dtypes.float32) - dropout = nn_ops.dropout(t, keep_prob, noise_shape=[x_dim, 1]) + dropout = nn_ops.dropout(t, rate=(1 - keep_prob), noise_shape=[x_dim, 1]) self.assertEqual([x_dim, y_dim], dropout.get_shape()) final_count = 0 for _ in xrange(0, num_iter): @@ -364,7 +364,7 @@ class DropoutTest(test_lib.TestCase): num_iter = 10 for keep_prob in [0.1, 0.5, 0.8]: t = constant_op.constant(1.0, shape=[x_dim, y_dim], dtype=dtypes.float32) - dropout = nn_ops.dropout(t, keep_prob, noise_shape=[x_dim, 1]) + dropout = nn_ops.dropout(t, rate=(1 - keep_prob), noise_shape=[x_dim, 1]) self.assertEqual([x_dim, y_dim], dropout.get_shape()) for _ in xrange(0, num_iter): value = self.evaluate(dropout) @@ -409,7 +409,7 @@ class DropoutTest(test_lib.TestCase): keep_prob = 0.5 x = constant_op.constant(1.0, shape=[x_dim, y_dim], dtype=dtypes.float32) dropout_x = nn_ops.dropout( - x, keep_prob, noise_shape=array_ops.placeholder(dtypes.int32)) + x, rate=(1- keep_prob), noise_shape=array_ops.placeholder(dtypes.int32)) self.assertEqual(x.get_shape(), dropout_x.get_shape()) def testPartialShapedDropout(self): @@ -419,7 +419,7 @@ class DropoutTest(test_lib.TestCase): for keep_prob in [0.1, 0.5, 0.8]: t = constant_op.constant(1.0, shape=[x_dim, y_dim], dtype=dtypes.float32) # Set noise_shape=[None, 1] which means [x_dim, 1]. - dropout = nn_ops.dropout(t, keep_prob, noise_shape=[None, 1]) + dropout = nn_ops.dropout(t, rate=(1- keep_prob), noise_shape=[None, 1]) self.assertEqual([x_dim, y_dim], dropout.get_shape()) final_count = 0 for _ in xrange(0, num_iter): @@ -478,22 +478,22 @@ class DropoutTest(test_lib.TestCase): keep_prob = 0.5 t = constant_op.constant(1.0, shape=[x_dim, y_dim], dtype=dtypes.float32) with self.assertRaises(ValueError): - _ = nn_ops.dropout(t, keep_prob, noise_shape=[x_dim, y_dim + 10]) + _ = nn_ops.dropout(t, rate=(1 - keep_prob), noise_shape=[x_dim, y_dim + 10]) with self.assertRaises(ValueError): - _ = nn_ops.dropout(t, keep_prob, noise_shape=[x_dim, y_dim, 5]) + _ = nn_ops.dropout(t, rate=(1 - keep_prob), noise_shape=[x_dim, y_dim, 5]) with self.assertRaises(ValueError): - _ = nn_ops.dropout(t, keep_prob, noise_shape=[x_dim + 3]) + _ = nn_ops.dropout(t, rate=(1 - keep_prob), noise_shape=[x_dim + 3]) with self.assertRaises(ValueError): - _ = nn_ops.dropout(t, keep_prob, noise_shape=[x_dim]) + _ = nn_ops.dropout(t, rate=(1 - keep_prob), noise_shape=[x_dim]) # test that broadcasting proceeds - _ = nn_ops.dropout(t, keep_prob, noise_shape=[y_dim]) - _ = nn_ops.dropout(t, keep_prob, noise_shape=[1, y_dim]) - _ = nn_ops.dropout(t, keep_prob, noise_shape=[x_dim, 1]) - _ = nn_ops.dropout(t, keep_prob, noise_shape=[1, 1]) + _ = nn_ops.dropout(t, rate=(1 - keep_prob), noise_shape=[y_dim]) + _ = nn_ops.dropout(t, rate=(1 - keep_prob), noise_shape=[1, y_dim]) + _ = nn_ops.dropout(t, rate=(1 - keep_prob), noise_shape=[x_dim, 1]) + _ = nn_ops.dropout(t, rate=(1 - keep_prob), noise_shape=[1, 1]) def testNoDropoutFast(self): x = array_ops.zeros((5,)) - y = nn_ops.dropout(x, keep_prob=1) + y = nn_ops.dropout(x, rate=0) self.assertTrue(x is y) y = nn_ops.dropout_v2(x, rate=0)