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Searched refs:x_shape (Results 1 – 25 of 76) sorted by relevance

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/external/tensorflow/tensorflow/cc/gradients/
Darray_grad_test.cc35 void RunTest(const Output& x, const TensorShape& x_shape, const Output& y, in RunTest() argument
40 scope_, {x}, {x_shape}, {y}, {y_shape}, &max_error))); in RunTest()
57 TensorShape x_shape({1, 2, 3}); in TEST_F() local
59 xs.push_back(Placeholder(scope_, DT_FLOAT, Placeholder::Shape(x_shape))); in TEST_F()
60 xs.push_back(Placeholder(scope_, DT_FLOAT, Placeholder::Shape(x_shape))); in TEST_F()
63 RunTest(xs, {x_shape, x_shape}, {y}, {y_shape}); in TEST_F()
67 TensorShape x_shape({1, 2, 3}); in TEST_F() local
69 xs.push_back(Placeholder(scope_, DT_FLOAT, Placeholder::Shape(x_shape))); in TEST_F()
70 xs.push_back(Placeholder(scope_, DT_FLOAT, Placeholder::Shape(x_shape))); in TEST_F()
73 RunTest(xs, {x_shape, x_shape}, {y}, {y_shape}); in TEST_F()
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Dnn_grad_test.cc54 void RunTest(const Output& x, const TensorShape& x_shape, const Output& y, in RunTest() argument
58 scope_, {x}, {x_shape}, {y}, {y_shape}, &max_error))); in RunTest()
211 TensorShape x_shape({5, 2}); in TEST_F() local
213 auto x = Placeholder(scope_, DT_FLOAT, Placeholder::Shape(x_shape)); in TEST_F()
215 RunTest(x, x_shape, y, y_shape); in TEST_F()
237 TensorShape x_shape({1, 2, 2, 1}); in TEST_F() local
239 auto x = Placeholder(scope_, DT_FLOAT, Placeholder::Shape(x_shape)); in TEST_F()
244 Tensor x_init_value = Tensor(DT_FLOAT, x_shape); in TEST_F()
250 TensorShape x_shape({1, 2, 2, 1}); in TEST_F() local
252 auto x = Placeholder(scope_, DT_FLOAT, Placeholder::Shape(x_shape)); in TEST_F()
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Dmath_grad_test.cc580 TensorShape x_shape = shapes[0]; in TestMatMulGrad() local
584 Placeholder(root_, DataTypeToEnum<T>::v(), Placeholder::Shape(x_shape)); in TestMatMulGrad()
596 root_, {x, y}, {x_shape, y_shape}, {z}, {z_shape}, &max_error))); in TestMatMulGrad()
609 TensorShape x_shape; in RandMatMulShapes() local
612 x_shape = tx ? TensorShape({b, k, m}) : TensorShape({b, m, k}); in RandMatMulShapes()
615 x_shape = tx ? TensorShape({k, m}) : TensorShape({m, k}); in RandMatMulShapes()
617 shapes->push_back(x_shape); in RandMatMulShapes()
735 TensorShape x_shape({2, 3, 5, 7}); in TEST_F() local
736 auto x = Placeholder(scope_, DT_FLOAT, Placeholder::Shape(x_shape)); in TEST_F()
740 RunTest({x}, {x_shape}, {y}, {y_shape}); in TEST_F()
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Dimage_grad_test.cc81 TensorShape x_shape({1, 2, 2, 1}); in TestResizedShapeForType() local
82 Tensor x_data = MakeData<T>(x_shape); in TestResizedShapeForType()
114 TensorShape x_shape({1, 4, 6, 1}); in TestResizeToSmallerAndAlign() local
115 Tensor x_data = MakeData<X_T>(x_shape); in TestResizeToSmallerAndAlign()
129 TensorShape x_shape({1, 2, 3, 1}); in TestResizeToLargerAndAlign() local
130 Tensor x_data = MakeData<X_T>(x_shape); in TestResizeToLargerAndAlign()
211 void TestScaleAndTranslate(const TensorShape x_shape, const int out_height, in TestScaleAndTranslate() argument
215 Tensor x_data = MakeData<X_T>(x_shape); in TestScaleAndTranslate()
326 TensorShape x_shape({1, 4, 2, 1}); in TestCropAndResize() local
327 Tensor x_data = MakeData<X_T>(x_shape); in TestCropAndResize()
/external/tensorflow/tensorflow/python/ops/
Dnn_fused_batchnorm_test.py57 x_shape, argument
64 x_val = np.random.random_sample(x_shape).astype(x_dtype)
109 x_shape, argument
116 x_val = np.random.random_sample(x_shape).astype(x_dtype)
144 def _compute_gradient_error_float16(self, x, x32, x_shape, y, y32, y_shape): argument
166 x_init_val = np.random.random_sample(x_shape).astype(np.float16)
172 x, x_shape, y, y_shape, delta=1e-3, x_init_value=x_init_val)
174 x32, x_shape, y32, y_shape, delta=1e-3, x_init_value=x32_init_val)
182 x_shape, argument
190 x_val = np.random.random_sample(x_shape).astype(x_dtype)
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Dgradient_checker.py56 def _compute_theoretical_jacobian(x, x_shape, x_data, dy, dy_shape, dx, argument
83 x_shape = tuple(x_shape) + (2,)
87 x_size = _product(x_shape)
88 x_val_size = _product(x_shape[1:]) # This is used for sparse gradients
134 def _compute_numeric_jacobian(x, x_shape, x_data, y, y_shape, delta, argument
168 x_size = _product(x_shape) * (2 if x.dtype.is_complex else 1)
211 x_shape, argument
229 assert(list(x_shape) == i_shape), "x_shape = %s, init_data shape = %s" % (
230 x_shape, i_shape)
233 x_data = np.random.random_sample(x_shape).astype(t.as_numpy_dtype)
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Dimage_ops_test.py359 x_shape = [2, 2, 3]
361 x_np = np.array(x_data, dtype=np.uint8).reshape(x_shape)
365 y_np = np.array(y_data, dtype=np.uint8).reshape(x_shape)
368 x = constant_op.constant(x_np, shape=x_shape)
374 x_shape = [2, 2, 3]
376 x_np = np.array(x_data, dtype=np.uint8).reshape(x_shape)
380 y_np = np.array(y_data, dtype=np.uint8).reshape(x_shape)
383 x = constant_op.constant(x_np, shape=x_shape)
389 x_shape = [2, 1, 2, 3]
391 x_np = np.array(x_data, dtype=np.uint8).reshape(x_shape)
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Dnn_batchnorm_test.py76 x_shape = [3, 5, 4, 2]
78 x_val = np.random.random_sample(x_shape).astype(np.float32)
125 x_shape = [3, 5, 4, 5]
128 x_val = np.random.random_sample(x_shape).astype(np.float64)
151 all_shapes = [x_shape, param_shape, param_shape, param_shape, param_shape]
154 output, x_shape)
210 x_shape = [7, 5, 4, 6]
213 x_val = np.random.random_sample(x_shape).astype(np.float32)
218 backprop_val = np.random.random_sample(x_shape).astype(np.float32)
262 x_shape = (3, 5, 4, 2)
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Dnn_test.py56 x_shape = [5, 17]
57 x_np = np.random.randint(0, 2, size=x_shape).astype(np.float32)
61 x_tf.set_shape(x_shape)
107 x_shape = [5, 10]
108 x_np = np.random.randn(*x_shape).astype(np.float32)
133 def testGradient(self, x_shape): argument
134 x_np = np.random.randn(*x_shape).astype(np.float64)
138 err = gradient_checker.compute_gradient_error(x_tf, x_shape, y_tf,
139 x_shape)
155 x_shape = [5, 10]
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/external/tensorflow/tensorflow/compiler/tf2xla/kernels/
Dreverse_op.cc37 const TensorShape x_shape = ctx->InputShape(0); in Compile() local
43 OP_REQUIRES(ctx, revd_shape.num_elements() == x_shape.dims(), in Compile()
47 x_shape.DebugString(), ".")); in Compile()
57 for (int d = 0; d < x_shape.dims(); ++d) { in Compile()
75 const TensorShape x_shape = ctx->InputShape(0); in Compile() local
81 OP_REQUIRES(ctx, axes_shape.num_elements() <= x_shape.dims(), in Compile()
85 x_shape.DebugString(), ".")); in Compile()
97 absl::InlinedVector<bool, 8> witnessed_axes(x_shape.dims(), false); in Compile()
101 ctx, (-x_shape.dims() <= axes[d]) && (axes[d] < x_shape.dims()), in Compile()
103 x_shape.dims(), ", ", x_shape.dims(), ").")); in Compile()
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/external/tensorflow/tensorflow/python/kernel_tests/
Dconv1d_transpose_test.py40 x_shape = [2, 6, 3]
47 1.0, shape=x_shape, name="x", dtype=dtypes.float32)
68 x_shape = [2, 4, 3]
75 1.0, shape=x_shape, name="x", dtype=dtypes.float32)
82 for n in xrange(x_shape[0]):
97 x_shape = [2, 4, 3]
104 1.0, shape=x_shape, name="x", dtype=dtypes.float32)
116 for n in xrange(x_shape[0]):
135 x_shape = [2, 4, 3]
140 x_val = np.random.random_sample(x_shape).astype(np.float64)
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Dconv2d_transpose_test.py44 x_shape = [2, 6, 4, 3]
51 1.0, shape=x_shape, name="x", dtype=dtypes.float32)
64 for n in xrange(x_shape[0]):
82 x_shape = [2, 6, 4, 3]
89 1.0, shape=x_shape, name="x", dtype=dtypes.float32)
96 for n in xrange(x_shape[0]):
115 x_shape = [2, 6, 4, 3]
122 1.0, shape=x_shape, name="x", dtype=dtypes.float32)
134 for n in xrange(x_shape[0]):
160 x_shape = [2, 6, 4, 3]
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Dconv3d_transpose_test.py40 x_shape = [2, 5, 6, 4, 3]
47 1.0, shape=x_shape, name="x", dtype=dtypes.float32)
67 for n in xrange(x_shape[0]):
90 x_shape = [2, 5, 6, 4, 3]
97 1.0, shape=x_shape, name="x", dtype=dtypes.float32)
104 for n in xrange(x_shape[0]):
126 x_shape = [2, 2, 3, 4, 3]
131 x_value = np.random.random_sample(x_shape).astype(np.float64)
140 x_shape = [2, 5, 6, 4, 3]
145 1.0, shape=x_shape, name="x", dtype=dtypes.float32)
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Datrous_conv2d_test.py68 x_shape = [2, height, width, 2]
69 x = np.arange(np.prod(x_shape), dtype=np.float32).reshape(x_shape)
116 x_shape = [3, height, width, 2]
117 x = np.random.random_sample(x_shape).astype(np.float32)
145 x_shape = [2, 5, 6, 2]
152 x_val = np.random.random_sample(x_shape).astype(np.float32)
160 [x_shape, f_shape],
175 x_shape = [2, height, width, 2]
176 x = np.arange(np.prod(x_shape), dtype=np.float32).reshape(x_shape)
216 x_shape = [2, height, width, 2]
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Dnumerics_test.py37 x_shape = [5, 4]
38 x = np.random.random_sample(x_shape).astype(np.float32)
40 t = constant_op.constant(x, shape=x_shape, dtype=dtypes.float32)
46 x_shape = [5, 4]
47 x = np.random.random_sample(x_shape).astype(np.float32)
54 t = constant_op.constant(x, shape=x_shape, dtype=dtypes.float32)
62 t = constant_op.constant(x, shape=x_shape, dtype=dtypes.float32)
/external/tensorflow/tensorflow/core/kernels/
Dbetainc_op.cc49 const TensorShape& x_shape = x.shape(); in Compute() local
56 if (a_shape.dims() > 0 && x_shape.dims() > 0) { in Compute()
57 OP_REQUIRES(ctx, a_shape == x_shape, in Compute()
60 a_shape.DebugString(), " vs. ", x_shape.DebugString())); in Compute()
62 if (b_shape.dims() > 0 && x_shape.dims() > 0) { in Compute()
63 OP_REQUIRES(ctx, b_shape == x_shape, in Compute()
66 b_shape.DebugString(), " vs. ", x_shape.DebugString())); in Compute()
71 if (x_shape.dims() > 0) merged_shape = x_shape; in Compute()
76 if (a_shape == b_shape && a_shape == x_shape) { in Compute()
86 BCast x_shaper(BCast::FromShape(x_shape), merged_shape_vec); in Compute()
Dquantized_mul_op_test.cc38 void TestMul(const std::vector<int64>& x_shape, in TestMul() argument
46 Tensor x_float_tensor(DT_FLOAT, TensorShape(x_shape)); in TestMul()
87 void TestMulShape(const std::vector<int64>& x_shape, in TestMulShape() argument
89 const size_t x_num_elements = TensorShape(x_shape).num_elements(); in TestMulShape()
107 Tensor x_float_tensor(DT_FLOAT, TensorShape(x_shape)); in TestMulShape()
133 TestMul(x_shape, x_values, x_min_value, x_max_value, y_shape, y_values, in TestMulShape()
137 void TimeMul(const std::vector<int64>& x_shape, in TimeMul() argument
139 TestMulShape(x_shape, y_shape); in TimeMul()
143 Tensor x_quantized_tensor(DT_QUINT8, TensorShape(x_shape)); in TimeMul()
177 LOG(INFO) << "TimeMul: " << TensorShape(x_shape).DebugString() << " * " in TimeMul()
Dquantized_add_op_test.cc38 void TestAdd(const std::vector<int64>& x_shape, in TestAdd() argument
46 Tensor x_float_tensor(DT_FLOAT, TensorShape(x_shape)); in TestAdd()
87 void TestAddShape(const std::vector<int64>& x_shape, in TestAddShape() argument
89 const size_t x_num_elements = TensorShape(x_shape).num_elements(); in TestAddShape()
107 Tensor x_float_tensor(DT_FLOAT, TensorShape(x_shape)); in TestAddShape()
133 TestAdd(x_shape, x_values, x_min_value, x_max_value, y_shape, y_values, in TestAddShape()
137 void TimeAdd(const std::vector<int64>& x_shape, in TimeAdd() argument
139 TestAddShape(x_shape, y_shape); in TimeAdd()
143 Tensor x_quantized_tensor(DT_QUINT8, TensorShape(x_shape)); in TimeAdd()
177 LOG(INFO) << "TimeAdd: " << TensorShape(x_shape).DebugString() << " * " in TimeAdd()
/external/tensorflow/tensorflow/contrib/nn/python/ops/
Dscaled_softplus_test.py49 x_shape = [5, 10]
50 x_np = np.random.randn(*x_shape).astype(np.float32)
51 alpha_np = np.float32(np.random.rand(1, x_shape[1]) + 0.01)
52 clip_np = np.float32(np.random.rand(x_shape[0], 1) * 5.)
60 [x_shape, alpha_np.shape],
61 y_tf, x_shape,
66 [x_shape, alpha_np.shape, clip_np.shape],
67 z_tf, x_shape,
/external/tensorflow/tensorflow/cc/framework/
Dgradient_checker_test.cc126 TensorShape x_shape({4, 3}); in TEST() local
130 auto x = Placeholder(scope, DT_DOUBLE, Placeholder::Shape(x_shape)); in TEST()
135 scope, {x}, {x_shape}, {z}, {z_shape}, &max_error))); in TEST()
142 TensorShape x_shape({5, 2}); in TEST() local
143 auto x = Placeholder(scope, DT_DOUBLE, Placeholder::Shape(x_shape)); in TEST()
150 scope, {x}, {x_shape}, y.output, {y_shape, y_shape}, &max_error))); in TEST()
157 TensorShape x_shape({1, 2, 3}); in TEST() local
159 xs.push_back(Placeholder(scope, DT_DOUBLE, Placeholder::Shape(x_shape))); in TEST()
160 xs.push_back(Placeholder(scope, DT_DOUBLE, Placeholder::Shape(x_shape))); in TEST()
165 scope, xs, {x_shape, x_shape}, {y}, {y_shape}, &max_error))); in TEST()
/external/tensorflow/tensorflow/compiler/tests/
Dconv3d_test.py76 x_shape = [2, 5, 6, 4, 3]
83 1.0, shape=x_shape, name="x", dtype=dtypes.float32)
103 for n in xrange(x_shape[0]):
126 x_shape = [2, 5, 6, 4, 3]
133 1.0, shape=x_shape, name="x", dtype=dtypes.float32)
140 for n in xrange(x_shape[0]):
164 x_shape = [2, 5, 6, 4, 3]
171 1.0, shape=x_shape, name="x", dtype=dtypes.float32)
183 for n in xrange(x_shape[0]):
213 x_shape = [2, 3, 4, 3, 2]
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Dimage_ops_test.py120 x_shape = [1, 2, 2, 3]
122 x_np = np.array(x_data, dtype=np.float32).reshape(x_shape) / 255.
128 y_np = np.array(y_data, dtype=np.float32).reshape(x_shape) / 255.
133 x_shape = [2, 1, 2, 3]
135 x_np = np.array(x_data, dtype=np.uint8).reshape(x_shape)
138 y_np = np.array(y_data, dtype=np.uint8).reshape(x_shape)
163 for x_shape in x_shapes:
164 x_np = np.random.rand(*x_shape) * 255.
174 x_shape = [2, 2, 3]
176 x_np = np.array(x_data, dtype=np.uint8).reshape(x_shape)
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Dfused_batchnorm_test.py76 x_shape = [2, 2, 6, channel]
78 x_val = np.random.random_sample(x_shape).astype(np.float32)
117 x_shape = [2, 2, 6, channel]
119 x_val = np.random.random_sample(x_shape).astype(np.float32)
186 x_shape = [2, 2, 6, channel]
188 grad_val = np.random.random_sample(x_shape).astype(np.float32)
189 x_val = np.random.random_sample(x_shape).astype(np.float32)
256 x_shape = [2, 2, 6, channel]
258 grad_val = np.random.random_sample(x_shape).astype(np.float32)
259 x_val = np.random.random_sample(x_shape).astype(np.float32)
/external/tensorflow/tensorflow/contrib/distributions/python/kernel_tests/bijectors/
Dfill_triangular_test.py56 x_shape = tensor_shape.TensorShape([5, 4, 6])
61 x = array_ops.ones(shape=x_shape, dtype=dtypes.float32)
65 self.assertAllEqual(x_.shape.as_list(), x_shape.as_list())
67 y_shape_ = b.forward_event_shape(x_shape)
70 self.assertAllEqual(x_shape_.as_list(), x_shape.as_list())
73 b.forward_event_shape_tensor(x_shape.as_list()))
77 self.assertAllEqual(x_shape_tensor, x_shape.as_list())
/external/tensorflow/tensorflow/python/keras/utils/
Dkernelized_utils.py40 x_shape = x_matrix.shape
42 if y_shape[1] != x_shape[1]: # dimensions do not match.
45 'vs {}.'.format(y_shape[1], x_shape[1]))
50 array_ops.expand_dims(y_matrix, 0), [x_shape[0], 1, 1])

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