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Results 11 - 20 of 34 for broadcastable (0.34 sec)
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tensorflow/compiler/mlir/lite/stablehlo/transforms/fuse_convolution_pass.cc
if (!result_type) { return rewriter.notifyMatchFailure(mul_op, [&](::mlir::Diagnostic &diag) { diag << "entities 'filter, multiplier' failed to satisfy constraint: " "non-broadcastable operands"; }); } filter_value = filter.getValue(); mul_value = multiplier.getValue(); // In MHLO, Conv filter is in HWIO format, Depthwise conv filter is in HW1O
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 22 22:21:19 UTC 2024 - 8.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tf_optimize.mlir
// CHECK: return %[[CONV]] : tensor<1x28x23x2xf32> } // CHECK-LABEL: @notfuseMulIntoConv2d // filter and multiply are not broadcastable func.func @notfuseMulIntoConv2d(%arg0: tensor<1x112x112x3xf32>) -> tensor<1x28x23x2xf32> {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 9.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_ops_tensor_helper.cc
auto result_type = OpTrait::util::getBroadcastedType(x.getType(), y.getType()); if (!result_type) { if (incompatible_shape_error.getValue()) { mlir::emitError(loc, "non-broadcastable operands"); } else { return UnrankedTensorType::get(builder->getI1Type()); } } auto ranked_type = mlir::dyn_cast<RankedTensorType>(result_type);
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/quantization/tensorflow/passes/prepare_lifting.td
"$1.getType().cast<ShapedType>().hasRank() && " "$0.getType().cast<ShapedType>().getShape() == $1.getType().cast<ShapedType>().getShape()">, "Checks if the shapes of tensors are same.">; // Make the 1D value $0 broadcastable with the shape of $1. def MakeOneDimValueBroadcastable : NativeCodeCall< "MakeOneDimValueBroadcastable($_builder, $_loc, $0, $1.getType().cast<ShapedType>())">;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 14 03:24:59 UTC 2024 - 8.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/tests/legalize-tf-binary-elementwise.mlir
func.return %1: tensor<2xi32> } // CHECK-LABEL: func @broadcast_add // TODO(laurenzo): Change this to a (5 + 2x1) shaped add to make the check // patterns unambiguous and more interesting (once broadcastable trait is // fixed upstream). func.func @broadcast_add(%arg0: tensor<1xi32>, %arg1: tensor<1x2xi32>) -> tensor<1x2xi32> {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 15:32:52 UTC 2024 - 18.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/prepare_lifting.cc
binding_output = op->getResult(0); binding_input = op->getOperand(0); binding_weight = op->getOperand(1); return success(); } // Makes the 1D value broadcastable with the `rhs_shape`. Value MakeOneDimValueBroadcastable(OpBuilder& builder, Location loc, Value value, ShapedType rhs_shape) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 17:58:54 UTC 2024 - 13.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/push_transpose_through_ewise.cc
} return new_shape; } // Determine if op commutes with transposes. Requires a strict // definition of Elementwise, all i/o shapes and types must be same-rank // broadcastable and fully static. Consider moving this into attribute later. bool IsElementwise(Operation *op) { if (!(llvm::isa<TFL::AddOp, TFL::MulOp, TFL::DivOp, TFL::SubOp, TFL::MaximumOp, TFL::MinimumOp>(op))) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 12.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_executor.cc
tf_type::DropRefAndSubTypes(output_tensor_type)); if (!broadcasted_type) { return switchn.emitOpError() << "expects data operand to be broadcastable with all output types" << " but got " << operand0_tensor_type << " vs " << output_tensor_type; } } return success(); } void SwitchNOp::print(OpAsmPrinter &p) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 42.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/optimize.cc
bool IsBroadcastableElementsAttrAndType(Type a, Type b) { return OpTrait::util::getBroadcastedType(a, b) != Type(); } // Returns whether the resultant type of any broadcastable operation with // operands `a` and `b` matches `expected_output`. Returns false if `a` is not // broadcast-compatible with `b`. bool OperandsBroadcastToOutputType(Type a, Type b, Type expected_output) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 00:40:15 UTC 2024 - 102.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/transforms/legalize_tf_patterns.td
//===----------------------------------------------------------------------===// // Check that two values can be broadcasted together def AreBroadcastCompatible : Constraint<CPred<"AreBroadcastCompatible($0, $1)">, "types must be broadcastable">; class DirectBinaryPat<Op FromOp, Op ToOp> : Pat<(FromOp AnyTensor:$l, AnyTensor:$r), (ToOp $l, $r, (BinBroadcastDimensions $l, $r))>; foreach fromToBinPair = [[TF_AddV2Op, CHLO_BroadcastAddOp],
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon May 06 18:46:23 UTC 2024 - 34.8K bytes - Viewed (0)