| /external/tensorflow/tensorflow/python/kernel_tests/ |
| conv1d_transpose_test.py | 44 f_shape = [3, 2, 3]
49 1.0, shape=f_shape, name="filter", dtype=dtypes.float32)
72 f_shape = [3, 2, 3]
77 1.0, shape=f_shape, name="filter", dtype=dtypes.float32)
83 for k in xrange(f_shape[1]):
101 f_shape = [3, 2, 3]
106 1.0, shape=f_shape, name="filter", dtype=dtypes.float32)
117 for k in xrange(f_shape[1]):
136 f_shape = [3, 2, 3]
141 f_val = np.random.random_sample(f_shape).astype(np.float64
[all...] |
| conv2d_transpose_test.py | 48 f_shape = [3, 3, 2, 3]
53 1.0, shape=f_shape, name="filter", dtype=dtypes.float32)
65 for k in xrange(f_shape[2]):
86 f_shape = [3, 3, 2, 3]
91 1.0, shape=f_shape, name="filter", dtype=dtypes.float32)
97 for k in xrange(f_shape[2]):
119 f_shape = [3, 3, 2, 3]
124 1.0, shape=f_shape, name="filter", dtype=dtypes.float32)
135 for k in xrange(f_shape[2]):
161 f_shape = [3, 3, 2, 3
[all...] |
| conv3d_transpose_test.py | 44 f_shape = [3, 3, 3, 2, 3]
49 1.0, shape=f_shape, name="filter", dtype=dtypes.float32)
68 for k in xrange(f_shape[3]):
94 f_shape = [3, 3, 3, 2, 3]
99 1.0, shape=f_shape, name="filter", dtype=dtypes.float32)
105 for k in xrange(f_shape[3]):
127 f_shape = [3, 3, 3, 2, 2]
132 f_value = np.random.random_sample(f_shape).astype(np.float64)
142 f_shape = [3, 3, 3, 2, 3]
147 1.0, shape=f_shape, name="filter", dtype=dtypes.float32
[all...] |
| atrous_conv2d_test.py | 74 f_shape = [kernel_height, kernel_width, 2, 2]
75 f = np.arange(np.prod(f_shape), dtype=np.float32).reshape(f_shape)
121 f_shape = [kernel, kernel, 2, 2]
122 f = 1e-2 * np.random.random_sample(f_shape).astype(np.float32)
147 f_shape = [3, 3, 2, 2]
153 f_val = np.random.random_sample(f_shape).astype(np.float32)
160 [x_shape, f_shape],
181 f_shape = [kernel_height, kernel_width, 2, 2]
182 f = np.arange(np.prod(f_shape), dtype=np.float32).reshape(f_shape
[all...] |
| conv1d_test.py | 64 f_shape = [3, 2, 3]
69 1.0, shape=f_shape, name="filter", dtype=dtypes.float32)
80 for k in xrange(f_shape[1]):
|
| atrous_convolution_test.py | 217 f_shape = [kernel, kernel, 2, 2]
218 f1 = 1e-2 * np.random.random_sample(f_shape).astype(np.float32)
219 f2 = 1e-2 * np.random.random_sample(f_shape).astype(np.float32)
254 def _test_gradient(self, x_shape, f_shape, dilation_rate, padding):
256 f_val = np.random.random_sample(f_shape).astype(np.float32)
262 err = gradient_checker.compute_gradient_error([x, f], [x_shape, f_shape],
275 f_shape=[3, 3, 2, 2],
|
| /external/tensorflow/tensorflow/compiler/tests/ |
| conv3d_test.py | 80 f_shape = [3, 3, 3, 2, 3]
85 1.0, shape=f_shape, name="filter", dtype=dtypes.float32)
104 for k in xrange(f_shape[3]):
130 f_shape = [3, 3, 3, 2, 3]
135 1.0, shape=f_shape, name="filter", dtype=dtypes.float32)
141 for k in xrange(f_shape[3]):
168 f_shape = [3, 3, 3, 2, 3]
173 1.0, shape=f_shape, name="filter", dtype=dtypes.float32)
184 for k in xrange(f_shape[3]):
214 f_shape = [3, 3, 3, 2, 2
[all...] |
| /external/tensorflow/tensorflow/python/grappler/ |
| tf_optimizer_test.py | 114 f_shape = array_ops.shape(f)
116 ops.add_to_collection('train_op', f_shape)
|
| /external/tensorflow/tensorflow/compiler/xla/service/ |
| algebraic_simplifier_test.cc | [all...] |
