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/external/tensorflow/tensorflow/lite/kernels/internal/reference/
Dprocess_broadcast_shapes.h96 params->broadcast_shape[0] = 1; in ProcessBroadcastShapes()
97 params->broadcast_shape[1] = 1; in ProcessBroadcastShapes()
98 params->broadcast_shape[2] = 1; in ProcessBroadcastShapes()
99 params->broadcast_shape[3] = 1; in ProcessBroadcastShapes()
100 params->broadcast_shape[4] = 1; in ProcessBroadcastShapes()
104 params->broadcast_shape[4] *= shape_b->Dims(i); in ProcessBroadcastShapes()
110 params->broadcast_shape[3] *= shape_b->Dims(i); in ProcessBroadcastShapes()
114 params->broadcast_shape[2] *= shape_a->Dims(i); in ProcessBroadcastShapes()
119 params->broadcast_shape[1] *= shape_a->Dims(i); in ProcessBroadcastShapes()
123 params->broadcast_shape[0] *= shape_b->Dims(i); in ProcessBroadcastShapes()
Dadd.h389 int y0 = params.broadcast_shape[0]; in BroadcastAddFivefold()
390 int y1 = params.broadcast_shape[1]; in BroadcastAddFivefold()
391 int y2 = params.broadcast_shape[2]; in BroadcastAddFivefold()
392 int y3 = params.broadcast_shape[3]; in BroadcastAddFivefold()
393 int y4 = params.broadcast_shape[4]; in BroadcastAddFivefold()
/external/tensorflow/tensorflow/compiler/tf2xla/lib/
Dbroadcast.cc50 std::vector<int64> broadcast_shape; in BroadcastTo() local
63 broadcast_dims.push_back(broadcast_shape.size()); in BroadcastTo()
65 broadcast_shape.push_back(*output_it); in BroadcastTo()
70 broadcast_shape.push_back(*input_it); in BroadcastTo()
71 broadcast_shape.push_back(*output_it / *input_it); in BroadcastTo()
75 broadcast_shape.push_back(*output_it); in BroadcastTo()
81 int broadcast_shape_size = broadcast_shape.size(); in BroadcastTo()
85 absl::c_reverse(broadcast_shape); in BroadcastTo()
87 xla::BroadcastInDim(input, broadcast_shape, broadcast_dims); in BroadcastTo()
88 if (broadcast_shape != output_dims) { in BroadcastTo()
/external/tensorflow/tensorflow/python/ops/linalg/
Dlinear_operator_tridiag.py216 broadcast_shape = array_ops.broadcast_static_shape(
219 broadcast_shape = array_ops.broadcast_static_shape(
220 broadcast_shape,
222 d_shape = broadcast_shape.concatenate(self.diagonals[1].shape[-1])
232 broadcast_shape = array_ops.broadcast_dynamic_shape(
235 broadcast_shape = array_ops.broadcast_dynamic_shape(
236 broadcast_shape,
239 [broadcast_shape, [array_ops.shape(self.diagonals[1])[-1]]], axis=0)
318 broadcast_shape = array_ops.broadcast_dynamic_shape(
322 [broadcast_shape, rhs_shape[-2:]], axis=-1))
[all …]
Dlinear_operator_permutation.py219 broadcast_shape = array_ops.broadcast_dynamic_shape(
222 broadcast_x_shape = array_ops.concat([broadcast_shape, [k]], axis=-1)
224 perm = array_ops.broadcast_to(perm, broadcast_shape)
Dlinear_operator_kronecker.py263 batch_shape = common_shapes.broadcast_shape(
386 broadcast_batch_shape = common_shapes.broadcast_shape(
503 broadcast_batch_shape = common_shapes.broadcast_shape(
Dlinear_operator_composition.py216 batch_shape = common_shapes.broadcast_shape(
/external/tensorflow/tensorflow/python/ops/
Drandom_grad.py197 broadcast_shape = array_ops.broadcast_dynamic_shape(
199 broadcast_shape = array_ops.broadcast_dynamic_shape(
200 minval_shape, broadcast_shape)
201 broadcast_shape = array_ops.broadcast_dynamic_shape(
202 maxval_shape, broadcast_shape)
204 array_ops.size(shape) - array_ops.size(broadcast_shape))
212 broadcast_shape, mean_shape)
214 broadcast_shape, stddev_shape)
216 broadcast_shape, minval_shape)
218 broadcast_shape, maxval_shape)
Darray_grad.py1186 broadcast_shape = op.inputs[1]
1188 if not isinstance(broadcast_shape, ops.EagerTensor):
1191 …broadcast_shape.graph._c_graph, broadcast_shape._as_tf_output())) # pylint: disable=protected-acc…
1193 broadcast_shape = constant_op.constant(
1196 broadcast_shape, input_value_shape)
Dclustering_ops.py478 broadcast_shape = array_ops.concat([
486 array_ops.reshape(count_updates, broadcast_shape),
490 learning_rate = array_ops.reshape(learning_rate, broadcast_shape)
Dstateless_random_ops.py409 broadcast_shape = array_ops.broadcast_dynamic_shape(
411 alpha_broadcast = array_ops.broadcast_to(alpha, broadcast_shape)
Drandom_ops.py631 broadcast_shape = array_ops.broadcast_dynamic_shape(
633 alpha_broadcast = array_ops.broadcast_to(alpha, broadcast_shape)
/external/tensorflow/tensorflow/compiler/tf2xla/kernels/
Dxla_broadcast_helper_op.cc81 std::vector<int64> broadcast_shape(max_rank_shape->dims(), 1LL); in Compile() local
85 context, dim >= 0 && dim < broadcast_shape.size(), in Compile()
90 broadcast_shape[dim] = min_rank_shape->dim_size(i); in Compile()
93 lhs = xla::BroadcastInDim(lhs, broadcast_shape, broadcast_dims); in Compile()
95 rhs = xla::BroadcastInDim(rhs, broadcast_shape, broadcast_dims); in Compile()
Dimage_resize_ops.cc220 xla::Shape broadcast_shape = broadcast_shape_or_status.ValueOrDie(); in BroadcastSpatialDimensions() local
223 broadcast_shape.set_dimensions(spatial_dimensions_offset + i, in BroadcastSpatialDimensions()
227 return xla::BroadcastInDim(input, broadcast_shape.dimensions(), in BroadcastSpatialDimensions()
/external/tensorflow/tensorflow/python/framework/
Dcommon_shapes_test.py44 common_shapes.broadcast_shape(shape1, shape2)
46 common_shapes.broadcast_shape(shape2, shape1)
58 expected, common_shapes.broadcast_shape(shape1, shape2))
60 expected, common_shapes.broadcast_shape(shape2, shape1))
62 self.assertEqual(expected, common_shapes.broadcast_shape(shape1, shape2))
63 self.assertEqual(expected, common_shapes.broadcast_shape(shape2, shape1))
133 actual_dims = common_shapes.broadcast_shape(shape1, shape2).dims
134 reflexive_actual_dims = common_shapes.broadcast_shape(shape2, shape1).dims
Dcommon_shapes.py89 def broadcast_shape(shape_x, shape_y): function
Dtensor_spec.py271 common_shapes.broadcast_shape(
279 common_shapes.broadcast_shape(
/external/tensorflow/tensorflow/python/ops/linalg/sparse/
Dconjugate_gradient.py111 broadcast_shape = array_ops.broadcast_dynamic_shape(
115 broadcast_shape = array_ops.broadcast_dynamic_shape(
116 broadcast_shape,
120 broadcast_shape, [array_ops.shape(rhs)[-1]]], axis=-1)
/external/tensorflow/tensorflow/compiler/mlir/tensorflow/transforms/
Doptimize.cc75 ArrayRef<int64_t> broadcast_shape = output_type.getShape(); in matchAndRewrite() local
77 input_shape_extended.append(broadcast_shape.size() - input_shape.size(), 1); in matchAndRewrite()
85 int64_t dim = broadcast_shape[i]; in matchAndRewrite()
/external/tensorflow/tensorflow/compiler/mlir/tfr/examples/mnist/
Dops_defs.py88 broadcast_shape = tf.shape(y)
91 s0=broadcast_shape, s1=input_value_shape)
152 broadcast_shape = tf.shape(y)
155 s0=broadcast_shape, s1=input_value_shape)
/external/tensorflow/tensorflow/python/ops/distributions/
Duniform.py189 broadcast_shape = array_ops.broadcast_dynamic_shape(
191 zeros = array_ops.zeros(broadcast_shape, dtype=self.dtype)
192 ones = array_ops.ones(broadcast_shape, dtype=self.dtype)
Dbijector_impl.py1056 broadcast_shape = array_ops.broadcast_static_shape(ildj.shape, y_shape)
1058 broadcast_shape[: broadcast_shape.ndims - (
/external/tensorflow/tensorflow/core/kernels/rnn/
Dgru_ops.h96 Eigen::array<Eigen::DenseIndex, 2> broadcast_shape({batch_size_, 1}); in operator()
98 r_u_bar.device(d) += b_ru.reshape(b_ru_shape).broadcast(broadcast_shape); in operator()
116 c.device(d) += (b_c.reshape(b_c_shape).broadcast(broadcast_shape)); in operator()
/external/tensorflow/tensorflow/python/kernel_tests/random/
Drandom_binomial_test.py180 broadcast_shape = counts.shape
188 return np.reshape(moments, broadcast_shape)
/external/tensorflow/tensorflow/python/keras/layers/
Dnormalization.py786 broadcast_shape = [1] * ndims
787 broadcast_shape[self.axis[0]] = input_shape.dims[self.axis[0]].value
792 return array_ops.reshape(v, broadcast_shape)
1213 broadcast_shape = [1] * ndims
1215 broadcast_shape[dim] = input_shape.dims[dim].value
1219 return array_ops.reshape(v, broadcast_shape)

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