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/external/tensorflow/tensorflow/python/kernel_tests/
Dconv2d_transpose_test.py44 y_shape = [2, 6, 4, 2]
54 x, f, y_shape, strides=strides, padding="SAME")
65 for w in xrange(y_shape[2]):
66 for h in xrange(y_shape[1]):
68 h_in = h > 0 and h < y_shape[1] - 1
69 w_in = w > 0 and w < y_shape[2] - 1
82 y_shape = [2, 12, 8, 2]
92 x, f, y_shape, strides=strides, padding="SAME")
97 for w in xrange(y_shape[2]):
98 for h in xrange(y_shape[1]):
[all …]
Dconv3d_transpose_test.py40 y_shape = [2, 5, 6, 4, 2]
50 x, f, y_shape, strides=strides, padding="SAME")
68 for w in xrange(y_shape[3]):
69 for h in xrange(y_shape[2]):
70 for d in xrange(y_shape[1]):
71 d_in = d > 0 and d < y_shape[1] - 1
72 h_in = h > 0 and h < y_shape[2] - 1
73 w_in = w > 0 and w < y_shape[3] - 1
90 y_shape = [2, 10, 12, 8, 2]
100 x, f, y_shape, strides=strides, padding="SAME")
[all …]
Dconv1d_test.py63 y_shape = [2, 9, 2]
73 x, f, y_shape, stride=stride, padding="VALID")
76 cache_values = np.zeros(y_shape, dtype=np.float32)
83 for w in xrange(pad, y_shape[1] - pad):
86 w_in = w % stride == 0 and w > pad and w < y_shape[1] - 1 - pad
Datrous_conv2d_test.py143 y_shape = [2, 5, 6, 2]
155 output, y_shape)
185 y_shape = [2, height, width, 2]
187 y_shape = [
192 y1 = nn_ops.atrous_conv2d_transpose(x, f, y_shape, rate,
195 x, f_up, y_shape, strides=[1, 1, 1, 1], padding=padding)
Dembedding_ops_test.py481 y_shape = [num_ids] + list(params[_PName(0) + ":0"].shape[1:])
486 x, x_shape, y, y_shape, x_init_value=x_init_value)
501 y_shape = [num_ids] + list(params[_PName(0) + ":0"].shape[1:])
506 x, x_shape, y, y_shape, x_init_value=x_init_value)
717 y_shape = [batch_size] + list(params[_PName(0) + ":0"].shape[1:])
719 x, x_shape, y, y_shape, x_init_value=x_init_value)
Datrous_convolution_test.py259 y_shape = output.get_shape().as_list()
261 output, y_shape)
/external/tensorflow/tensorflow/cc/gradients/
Darray_grad_test.cc36 const TensorShape& y_shape) { in RunTest() argument
40 scope_, {x}, {x_shape}, {y}, {y_shape}, &max_error))); in RunTest()
62 TensorShape y_shape({2, 1, 2, 3}); in TEST_F() local
63 RunTest(xs, {x_shape, x_shape}, {y}, {y_shape}); in TEST_F()
72 TensorShape y_shape({1, 2, 2, 3}); in TEST_F() local
73 RunTest(xs, {x_shape, x_shape}, {y}, {y_shape}); in TEST_F()
107 TensorShape y_shape = TensorShape({5, 1}); in TEST_F() local
108 RunTest({x}, {x_shape}, y.output, {y_shape, y_shape}); in TEST_F()
115 TensorShape y_shape({5, 2, 5, 2}); in TEST_F() local
116 RunTest(x, x_shape, y, y_shape); in TEST_F()
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Dnn_grad_test.cc47 const TensorShape& y_shape) { in RunTest() argument
50 scope_, {x}, {x_shape}, {y}, {y_shape}, &max_error))); in RunTest()
55 const TensorShape& y_shape) { in RunTest() argument
58 scope_, x, x_init_value, y, y_shape, &max_error))); in RunTest()
156 TensorShape y_shape({1}); in TEST_F() local
159 RunTest(x, x_shape, y, y_shape); in TEST_F()
182 TensorShape y_shape({1, 1, 1, 1}); in TEST_F() local
190 RunTest(x, x_init_value, y, y_shape); in TEST_F()
195 TensorShape y_shape({1, 1, 1, 1}); in TEST_F() local
203 RunTest(x, x_init_value, y, y_shape); in TEST_F()
Dmath_grad_test.cc583 TensorShape y_shape = shapes[1]; in TestMatMulGrad() local
588 Placeholder(root_, DataTypeToEnum<T>::v(), Placeholder::Shape(y_shape)); in TestMatMulGrad()
598 root_, {x, y}, {x_shape, y_shape}, {z}, {z_shape}, &max_error))); in TestMatMulGrad()
621 TensorShape y_shape; in RandMatMulShapes() local
624 y_shape = ty ? TensorShape({b, n, k}) : TensorShape({b, k, n}); in RandMatMulShapes()
627 y_shape = ty ? TensorShape({n, k}) : TensorShape({k, n}); in RandMatMulShapes()
629 shapes->push_back(y_shape); in RandMatMulShapes()
725 const TensorShape& y_shape) { in RunTest() argument
729 scope_, x, x_init_value, y, y_shape, &max_error))); in RunTest()
741 TensorShape y_shape({2, 5}); in TEST_F() local
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Ddata_flow_grad_test.cc67 TensorShape y_shape({3, 2}); in TEST_F() local
68 RunTest(data, {d1_shape, d2_shape}, {y}, {y_shape}); in TEST_F()
/external/tensorflow/tensorflow/compiler/tests/
Dconv3d_test.py77 y_shape = [2, 5, 6, 4, 2]
87 x, f, y_shape, strides=strides, padding="SAME")
105 for w in xrange(y_shape[3]):
106 for h in xrange(y_shape[2]):
107 for d in xrange(y_shape[1]):
108 d_in = d > 0 and d < y_shape[1] - 1
109 h_in = h > 0 and h < y_shape[2] - 1
110 w_in = w > 0 and w < y_shape[3] - 1
127 y_shape = [2, 10, 12, 8, 2]
137 x, f, y_shape, strides=strides, padding="SAME")
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/external/tensorflow/tensorflow/compiler/tf2xla/lib/
Dbatch_dot.cc34 TF_ASSIGN_OR_RETURN(std::unique_ptr<xla::Shape> y_shape, in BatchDot()
39 if (xla::ShapeUtil::Rank(*x_shape) != xla::ShapeUtil::Rank(*y_shape)) { in BatchDot()
43 xla::ShapeUtil::HumanString(*y_shape)); in BatchDot()
55 if (x_shape->dimensions(i) != y_shape->dimensions(i)) { in BatchDot()
59 xla::ShapeUtil::HumanString(*y_shape)); in BatchDot()
66 if (x_shape->dimensions(x_inner_dim) != y_shape->dimensions(y_inner_dim)) { in BatchDot()
71 " vs. ", xla::ShapeUtil::HumanString(*y_shape), in BatchDot()
77 xla::ShapeUtil::HasZeroElements(*y_shape)) { in BatchDot()
85 dimensions.push_back(y_shape->dimensions(y_outer_dim)); in BatchDot()
94 if (y_shape->element_type() == xla::C64 && conjugate_y) { in BatchDot()
/external/tensorflow/tensorflow/python/ops/
Dgradient_checker.py134 def _compute_numeric_jacobian(x, x_shape, x_data, y, y_shape, delta, argument
168 y_size = _product(y_shape) * (2 if y.dtype.is_complex else 1)
194 def _compute_dx_and_dy(x, y, y_shape): argument
201 dy_orig = constant_op.constant(1.0, shape=y_shape, dtype=y.dtype)
213 y_shape, argument
237 x, x_shape, x_data, dy, y_shape, dx, extra_feed_dict=extra_feed_dict)
239 x, x_shape, x_data, y, y_shape, delta, extra_feed_dict=extra_feed_dict)
246 y_shape, argument
253 dx, dy = zip(*[_compute_dx_and_dy(xi, y, y_shape) for xi in x])
261 ret = [_compute_gradient(xi, x_shapei, dxi, y, y_shape, dyi, x_init_valuei,
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Dimage_ops_test.py1418 y_shape, argument
1421 target_height, target_width, _ = y_shape
1423 y = np.array(y).reshape(y_shape)
1468 y_shape = [2, 3, 1]
1470 self._assertReturns(x, x_shape, offset_height, offset_width, y, y_shape)
1473 y_shape = [3, 2, 1]
1475 self._assertReturns(x, x_shape, offset_height, offset_width, y, y_shape)
1478 y_shape = [2, 3, 1]
1480 self._assertReturns(x, x_shape, offset_height, offset_width, y, y_shape)
1483 y_shape = [3, 2, 1]
[all …]
Dsparse_grad.py189 y_shape = math_ops.to_int64(array_ops.shape(y))
191 array_ops.size(x_shape) - array_ops.size(y_shape), 0)
193 [array_ops.ones(num_added_dims, ops.dtypes.int64), y_shape], 0)
211 sparse_tensor.SparseTensor(scaled_indices, dy_val, y_shape))
/external/tensorflow/tensorflow/core/kernels/
Dquantized_mul_op_test.cc40 float x_max_value, const std::vector<int64>& y_shape, in TestMul() argument
56 Tensor y_float_tensor(DT_FLOAT, TensorShape(y_shape)); in TestMul()
88 const std::vector<int64>& y_shape) { in TestMulShape() argument
97 const size_t y_num_elements = TensorShape(y_shape).num_elements(); in TestMulShape()
111 Tensor y_float_tensor(DT_FLOAT, TensorShape(y_shape)); in TestMulShape()
133 TestMul(x_shape, x_values, x_min_value, x_max_value, y_shape, y_values, in TestMulShape()
138 const std::vector<int64>& y_shape, int64 iterations) { in TimeMul() argument
139 TestMulShape(x_shape, y_shape); in TimeMul()
148 Tensor y_quantized_tensor(DT_QUINT8, TensorShape(y_shape)); in TimeMul()
178 << TensorShape(y_shape).DebugString() in TimeMul()
Dquantized_add_op_test.cc40 float x_max_value, const std::vector<int64>& y_shape, in TestAdd() argument
56 Tensor y_float_tensor(DT_FLOAT, TensorShape(y_shape)); in TestAdd()
88 const std::vector<int64>& y_shape) { in TestAddShape() argument
97 const size_t y_num_elements = TensorShape(y_shape).num_elements(); in TestAddShape()
111 Tensor y_float_tensor(DT_FLOAT, TensorShape(y_shape)); in TestAddShape()
133 TestAdd(x_shape, x_values, x_min_value, x_max_value, y_shape, y_values, in TestAddShape()
138 const std::vector<int64>& y_shape, int64 iterations) { in TimeAdd() argument
139 TestAddShape(x_shape, y_shape); in TimeAdd()
148 Tensor y_quantized_tensor(DT_QUINT8, TensorShape(y_shape)); in TimeAdd()
178 << TensorShape(y_shape).DebugString() in TimeAdd()
/external/tensorflow/tensorflow/cc/framework/
Dgradient_checker_test.cc111 TensorShape y_shape({3, 2}); in TEST() local
115 auto y = Const(scope, {1.0, 2.0, 3.0, 4.0, 5.0, 6.0}, y_shape); in TEST()
131 TensorShape y_shape = TensorShape({5, 1}); in TEST() local
134 scope, {x}, {x_shape}, y.output, {y_shape, y_shape}, &max_error))); in TEST()
146 TensorShape y_shape({2, 1, 2, 3}); in TEST() local
149 scope, xs, {x_shape, x_shape}, {y}, {y_shape}, &max_error))); in TEST()
Dgradient_checker.cc114 for (const auto& y_shape : y_shapes) { in ComputeTheoreticalJacobianTranspose() local
117 ops::Cast(scope, ops::Const(scope, 1.0, y_shape), ys[0].type())); in ComputeTheoreticalJacobianTranspose()
394 const TensorShape& y_shape, JAC_T* max_error) { in ComputeGradientError() argument
399 scope, {x}, {x_datas[0].shape()}, {y}, {y_shape}, &x_datas, max_error); in ComputeGradientError()
409 const Output& y, const TensorShape& y_shape, JAC_T* max_error);
Dgradient_checker.h59 const TensorShape& y_shape, JAC_T* max_error);
/external/tensorflow/tensorflow/contrib/learn/python/learn/learn_io/
Ddata_feeder.py42 def _get_in_out_shape(x_shape, y_shape, n_classes, batch_size=None): argument
45 x_shape, dict), y_shape is not None and isinstance(y_shape, dict)
62 if y_shape is None:
76 output_shape = out_el_shape(y_shape, n_classes)
82 for k, v in list(y_shape.items())])
342 y_shape = dict([(k, v.shape) for k, v in list(self._y.items())
346 x_shape, y_shape, n_classes, batch_size)
839 y_shape = (x_count, len(self._y.columns))
844 x_shape, y_shape, n_classes, batch_size)
/external/tensorflow/tensorflow/tools/api/golden/
Dtensorflow.test.pbtxt25 …argspec: "args=[\'x\', \'x_shape\', \'y\', \'y_shape\', \'x_init_value\', \'delta\', \'init_target…
29 …argspec: "args=[\'x\', \'x_shape\', \'y\', \'y_shape\', \'x_init_value\', \'delta\', \'init_target…
/external/tensorflow/tensorflow/contrib/learn/python/learn/
Dmodels.py84 y_shape = y.get_shape()
85 if len(y_shape) == 1:
88 output_shape = y_shape[1]
/external/tensorflow/tensorflow/python/keras/_impl/keras/layers/
Dmerge.py162 y_shape = K.shape(y)
163 y_ndim = K.shape(y_shape)[0]
164 batch_size = y_shape[y_ndim - 1]
166 [K.expand_dims(batch_size), y_shape[:y_ndim - 1]])
/external/tensorflow/tensorflow/compiler/aot/
Dtest_graph_tfadd.pbtxt37 input : "y_shape"

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