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Results 1 - 10 of 29 for in_shape (0.65 sec)
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tensorflow/compiler/mlir/lite/utils/utils.h
std::vector<int64_t> in_shape{input_type.getShape().vec()}; std::vector<int64_t> out_shape{output_type.getShape().vec()}; // If the reshape changes the number of dimensions so it cannot be interpreted // as a transpose. if (in_shape.size() != out_shape.size()) { return false; } in_shape.erase(std::remove(in_shape.begin(), in_shape.end(), 1), in_shape.end());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 00:40:15 UTC 2024 - 11.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/internal/passes/extract_outside_compilation.cc
ArrayRef<int64_t> in_shape = ranked_type.getShape(); if (in_shape.empty() || in_shape[0] < 0) { return context_op->emitOpError() << "A map_outside_compilation op's input and output shapes must " "have rank at least one and the first dimension must be known."; } int64_t split_size = in_shape[0] / num_cores_per_replica; if (in_shape[0] % num_cores_per_replica != 0) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 21:25:12 UTC 2024 - 68.3K bytes - Viewed (0) -
tensorflow/cc/gradients/math_grad_test.cc
auto y = Sub(scope_, x1, x2); RunTest({x1, x2}, {x1_shape, x2_shape}, {y}, {x1_shape}); } TEST_F(NaryGradTest, Mul) { TensorShape x1_shape({3, 2, 5}); TensorShape x2_shape({2, 5}); auto x1 = Placeholder(scope_, DT_FLOAT, Placeholder::Shape(x1_shape)); auto x2 = Placeholder(scope_, DT_FLOAT, Placeholder::Shape(x2_shape)); auto y = Mul(scope_, x1, x2);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Aug 25 18:20:20 UTC 2023 - 36K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_ops_a_m.cc
// https://www.tensorflow.org/api_docs/cc/class/tensorflow/ops/batch-mat-mul int64_t x_row_dim = x_shape[x_shape.size() - 2]; int64_t x_col_dim = x_shape[x_shape.size() - 1]; int64_t y_row_dim = y_shape[y_shape.size() - 2]; int64_t y_col_dim = y_shape[y_shape.size() - 1]; int64_t out_row_dim = output_shape[output_shape.size() - 2]; int64_t out_col_dim = output_shape[output_shape.size() - 1];
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 146.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/python/integration_test/quantize_model_test_base.py
contracting_dims.add(c) x_signature = [ None if c not in contracting_dims else x_shape[cidx] for cidx, c in enumerate(x_labels) ] y_signature = [ None if c not in contracting_dims else y_shape[cidx] for cidx, c in enumerate(y_labels) ] return x_shape, y_shape, bias_shape, x_signature, y_signature def _create_einsum_model( self,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 06:31:57 UTC 2024 - 18.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/python/integration_test/quantize_model_test_base.py
x_signature = [ None if c not in contracting_dims else x_shape[cidx] for cidx, c in enumerate(x_labels) ] y_signature = [ None if c not in contracting_dims else y_shape[cidx] for cidx, c in enumerate(y_labels) ] return x_shape, y_shape, bias_shape, x_signature, y_signature def _create_einsum_model( self,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 21 08:51:46 UTC 2024 - 51.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/transforms/legalize_tf.cc
Value result = reduction.getResult(0); // The mean op needs to divide by the product of the reduced dimensions. if (std::is_same<OpTy, TF::MeanOp>::value) { Value in_shape = rewriter.create<shape::ShapeOfOp>(loc, op.getInput()); Value divisor_count = rewriter.create<arith::ConstantIndexOp>(loc, 1); for (size_t i = 0; i < input_shape.size(); ++i) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 20:00:43 UTC 2024 - 291.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/unfuse_mhlo_batch_norm.mlir
// CHECK-DAG: %[[RHS:.+]] = mhlo.subtract %[[OFFSET]], %[[MUL_MEAN]] : tensor<?xf32> // CHECK-DAG: %[[X_SHAPE:.+]] = shape.shape_of %[[X]] : tensor<?x?x?x?xf32> -> tensor<4xindex> // CHECK-DAG: %[[MULTIPLIER_BCAST:.+]] = "mhlo.dynamic_broadcast_in_dim"(%[[MULTIPLIER]], %[[X_SHAPE]]) <{broadcast_dimensions = dense<1> : tensor<1xi64>}> : (tensor<?xf32>, tensor<4xindex>) -> tensor<?x?x?x?xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 15:32:52 UTC 2024 - 10.4K bytes - Viewed (0) -
tensorflow/c/experimental/saved_model/internal/saved_model_api_test.cc
#include "tensorflow/c/experimental/saved_model/public/signature_def_param_list.h" #include "tensorflow/c/experimental/saved_model/public/tensor_spec.h" #include "tensorflow/c/tf_datatype.h" #include "tensorflow/c/tf_shape.h" #include "tensorflow/c/tf_status.h" #include "tensorflow/c/tf_tensor.h" #include "tensorflow/core/lib/io/path.h" #include "tensorflow/core/platform/status.h" #include "tensorflow/core/platform/stringpiece.h"
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 23 08:08:45 UTC 2024 - 21.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfr/ir/tfr_ops.cc
// TFR_ConstantTensorOp ( // ConstantOp (ConstAttr<F32Attr (in_scale[0] * in_scale[1] / // out_scale)) // ) // Currently, all decompositions using this pattern (Conv2D, FC) have the // following preconditions: // * out_scale: float scalar attribute // * in_scale[0] (input scale): float scalar, given by tf.Const -> tfr.cast // * in_scale[1] (filter scale): float scalar/vector
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Nov 21 16:55:41 UTC 2023 - 38.2K bytes - Viewed (0)