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tensorflow/cc/framework/gradient_checker_test.cc
xs.push_back(Placeholder(scope, DT_DOUBLE, Placeholder::Shape(shape))); xs.push_back(Placeholder(scope, DT_DOUBLE, Placeholder::Shape(shape))); auto tmp = Stack(scope, xs, Stack::Axis(0)); auto y = Unstack(scope, tmp, 2, Unstack::Axis(0)); double max_error; TF_ASSERT_OK((ComputeGradientError<double, double, double>( scope, xs, {shape, shape}, y.output, {shape, shape}, &max_error))); EXPECT_LT(max_error, 1e-10);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Aug 06 15:54:08 UTC 2018 - 6.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/optimize.cc
if (!axes_attr) return false; for (auto a : axes_attr.getValues<APInt>()) { int64_t axis = a.getSExtValue(); if (axis < 0) { axis += type_shape.size(); } if (axis < 0 || axis >= type_shape.size()) { // `axis` is not a valid axis in input. return false; } if (type_shape[axis] != 1) { return false; } } return true; }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 00:40:15 UTC 2024 - 102.3K bytes - Viewed (1) -
tensorflow/compiler/mlir/tensorflow/transforms/lower_tf.cc
// to expand at the given `axis`. Type InferExpandDimsType(Type ty, int64_t axis, Builder *builder) { auto ranked_ty = mlir::dyn_cast<RankedTensorType>(ty); // Unranked type. if (!ranked_ty) return ty; auto shape = llvm::to_vector<4>(ranked_ty.getShape()); if (axis < 0) axis += ranked_ty.getRank() + 1; shape.insert(shape.begin() + axis, 1);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 74.9K bytes - Viewed (0) -
tensorflow/c/experimental/ops/array_ops.cc
// // Description: // Given a tensor `input`, this operation inserts a dimension of 1 at the // dimension index `axis` of `input`'s shape. The dimension index `axis` // starts at zero; if you specify a negative number for `axis` it is counted // backward from the end. // // This operation is useful if you want to add a batch dimension to a single
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 10 19:11:36 UTC 2022 - 6.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/duplicate_shape_determining_constants.cc
// $group_assignment CompileTimeConstantOperand<TF::CrossReplicaSumOp, 1>, CompileTimeConstantOperand<TF::CumprodOp, 1>, // $axis CompileTimeConstantOperand<TF::CumsumOp, 1>, // $axis CompileTimeConstantOperand<TF::CumulativeLogsumexpOp, 1>, // $axis // $filter_sizes CompileTimeConstantOperand<TF::DepthwiseConv2dNativeBackpropFilterOp, 1>, // $input_sizes
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 22 05:52:39 UTC 2024 - 17.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/lift_quantizable_spots_as_functions_drq.td
[(IsNotInLiftedFunc $res), (IsConstTensor $b)], [], (addBenefit 1)>; def LiftGather : Pat< (TF_GatherV2Op:$res $params, $indices, $axis, $batch_dims), (LiftAsTFPartitionedCall<"composite_gather_fn"> (ArgumentList $params, $indices, $axis), (ResultList $res), (NamedAttributeList (NamedAttr<"batch_dims"> $batch_dims))), [(IsNotInLiftedFunc $res), (IsConstTensor $params)], [], (addBenefit 1)>;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sun Dec 10 05:52:02 UTC 2023 - 3.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/legalize_tf.cc
auto values = tf_concat_op.getValues(); auto output_type = tf_concat_op.getOutput().getType(); // Extract axis attribute from constant axis tensor ElementsAttr axis; if (!matchPattern(tf_concat_op.getAxis(), m_Constant(&axis))) return failure(); IntegerAttr axis_int = ExtractSingleElementAsInteger(axis); // "axis" operand could be a i64 tensor. Resolve it here. IntegerAttr axis_i32;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon May 20 20:06:54 UTC 2024 - 45.2K bytes - Viewed (1) -
tensorflow/compiler/mlir/tensorflow/tests/unroll-batch-matmul.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Dec 06 18:42:28 UTC 2023 - 63.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/transforms/legalize_tf.cc
int64_t depth = depth_attr.getValues<APInt>()[0].getSExtValue(); int64_t axis = op.getAxis(); if (axis == -1) axis = indices_shape.size(); llvm::SmallVector<int64_t, 4> broadcast_dims(indices_shape.size()); std::iota(broadcast_dims.begin(), broadcast_dims.begin() + axis, 0); std::iota(broadcast_dims.begin() + axis, broadcast_dims.end(), axis + 1); llvm::SmallVector<int64_t, 4> output_dims =
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 20:00:43 UTC 2024 - 291.8K bytes - Viewed (1) -
tensorflow/compiler/mlir/tensorflow/transforms/canonicalize.td
// Concat op patterns. //===----------------------------------------------------------------------===// def ConvertToConcatV2 : Pat< (TF_ConcatOp:$src $axis, $inputs), (TF_ConcatV2Op:$dest $inputs, $axis), [], [(CopyAttrs $src, $dest)]>; //===----------------------------------------------------------------------===// // Div op patterns.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Dec 06 18:42:28 UTC 2023 - 17K bytes - Viewed (0)