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Results 1 - 10 of 35 for set_shape (0.43 sec)
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tensorflow/compiler/mlir/tensorflow/ir/tf_ops_tensor_helper.cc
} } ArrayRef<int64_t> shape = ranked_ty.getShape(); SmallVector<int64_t, 4> out_shape; out_shape.reserve(rank - (keep_dims.getValue() ? 0 : num_reduce_dim)); for (int64_t i = 0; i < rank; ++i) { if (!is_reduce_dim[i]) out_shape.push_back(shape[i]); else if (keep_dims.getValue()) out_shape.push_back(1); } return RankedTensorType::get(out_shape, element_ty); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 6.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_ops_layout_helper.cc
ArrayRef<int64_t> shape = ranked_type.getShape(); assert(permutation.size() == shape.size()); SmallVector<int64_t, 4> new_shape(permutation.size()); for (size_t i = 0; i < permutation.size(); ++i) new_shape[i] = shape[permutation[i]]; return RankedTensorType::get(new_shape, ranked_type.getElementType()); } return type; }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 3.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tf_to_hlo_pipeline/sccp-post-shape-inference.mlir
%2 = "tf.PartitionedCall"(%1) {config = "", config_proto = "", executor_type = "", f = @get_shape} : (tensor<?x?xf32>) -> (tensor<?xi64>) // CHECK: return %[[RESULT]] func.return %2 : tensor<?xi64> } // CHECK-LABEL: func @get_shape func.func @get_shape(%arg0 : tensor<*xi64>) -> tensor<?xi64> { %0 = "tf.Shape"(%arg0) : (tensor<*xi64>) -> tensor<?xi64>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jul 25 02:54:34 UTC 2023 - 1020 bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/ir/UniformSupport.cc
if (auto tensor_type = dyn_cast<RankedTensorType>(input_type)) return RankedTensorType::get(tensor_type.getShape(), elemental_type); if (auto tensor_type = dyn_cast<UnrankedTensorType>(input_type)) return UnrankedTensorType::get(elemental_type); if (auto vector_type = dyn_cast<VectorType>(input_type)) return VectorType::get(vector_type.getShape(), elemental_type); // If the expressed types match, just use the new elemental type.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 08 02:10:16 UTC 2024 - 4.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/ir/tfl_canonicalize.td
def GetSqueezedPermutation: NativeCodeCall<"GetSqueezedPermutation($0, $1)">; // Check to see if the tensor dimensions can be Squeezed by eliminating 1s' def CanSqueezeTensor : Constraint<CPred< "GetShape($0).getNumElements() > GetSqueezedShape($0).getNumElements()">>; // Pattern to convert TFL_TransposeOp with rank>6 to rank<=6 if there are // redundant dimensions in the tensor. For example- [2x1x3] == [2x3] and 1 is
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Dec 13 20:41:03 UTC 2023 - 2.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/legacy_reshape.json
"outputs": [1], "operators": [ { "inputs": [ 0 ], "outputs": [ 1 ], "builtin_options_type": "ReshapeOptions", "builtin_options": { "new_shape": [ 2, 2 ] } } ] } ], "buffers": []
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 986 bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/batchmatmul_to_einsum.cc
auto rhs_type = mlir::dyn_cast<RankedTensorType>(input_rhs.getType()); if (!lhs_type || !rhs_type) return failure(); auto lhs_shape = lhs_type.getShape(); auto rhs_shape = rhs_type.getShape(); // Ensure that input ranks are at least 2. const int dims_a = lhs_shape.size(); const int dims_b = rhs_shape.size(); if (dims_a < 2 || dims_b < 2) { return failure();
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 3.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/fold_broadcast.cc
// Get the unbroadcasted shapes in the operand order. std::array<llvm::ArrayRef<int64_t>, 2> operand_shapes; operand_shapes[i] = broadcast_arg_type.getShape(); operand_shapes[1 - i] = argument_type.getShape(); // Check that the input of the broadcast and the other operand is broadcast // compatible. llvm::SmallVector<int64_t, 4> broadcasted_shape;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 7.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/utils/utils.td
def CreateNoneValue : NativeCodeCall< "$_builder.create<TFL::NoValueOp>($0.getLoc(), $_builder.getUnitAttr())">; // Returns shape of a ranked tensor. // if called without a ranked tensor it will fail. def GetShape: NativeCodeCall<"GetShape($0)">; // Constraint that values in list attribute are all ones. def IsAllOnesConstant : Constraint<CPred<"TFL::IsAllOnesConstant($0)">>;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 00:40:15 UTC 2024 - 4.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/utils/tf_to_xla_attribute_utils_test.cc
ShapedType packed_shape_type = mlir::dyn_cast<ShapedType>(packed_value.getType()); llvm::SmallVector<int64_t> packed_shape(packed_shape_type.getShape().begin(), packed_shape_type.getShape().end()); EXPECT_THAT(packed_shape, testing::ElementsAreArray(expected_packed_shape)); llvm::SmallVector<int8_t> packed_value_vector( packed_value_attr.getValues<int8_t>());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 3.5K bytes - Viewed (0)