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tensorflow/compiler/mlir/quantization/common/ir/QuantOps.td
<?x?x3x2>, axis=2 => N=6 ``` }]; let arguments = (ins quant_RealValueType:$arg, ElementsAttr:$layerStats, OptionalAttr<ElementsAttr>:$axisStats, OptionalAttr<I64Attr>:$axis); let results = (outs quant_RealValueType); let hasVerifier = 1; } def Quantization_CoupledRefOp : Quantization_Op<"coupled_ref", [SameOperandsAndResultType]> { let summary = [{
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jan 09 03:10:59 UTC 2024 - 10.2K bytes - Viewed (0) -
testing/internal-performance-testing/src/main/resources/org/gradle/reporting/performanceGraph.js
Registered: Wed Jun 12 18:38:38 UTC 2024 - Last Modified: Thu Apr 04 07:21:38 UTC 2024 - 6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/import_quant_stats_pass.cc
ElementsAttr axis_stats, IntegerAttr axis) { auto stats_op = b.create<quantfork::StatisticsOp>( b.getUnknownLoc(), res, layer_stats, axis_stats, axis); res.replaceAllUsesWith(stats_op); stats_op.getOperation()->replaceUsesOfWith(stats_op, res); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 08 10:41:08 UTC 2024 - 9.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/prepare_patterns.td
(UpdateShapeWithAxis<-1> $qtype, $old_value))), [(CanUpdateShapeWithAxis<-1> $qtype, $old_value)]>; // The axis is set to 0 because the transpose is from the legalization of // tf.conv2d and the new channel axis is the first dimension. def ReorderTransposeDequantQuantUsedByConv : Pat<(TF_TransposeOp:$old_value (TFL_DequantizeOp (TFL_QuantizeOp $input, $qtype)), $perm),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 00:40:15 UTC 2024 - 10.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/tests/e2e/device-transform-nnapi.mlir
%0 = "tfl.pack"(%arg0, %arg1) {axis = 0 : i32, values_count = 2 : i32} : (tensor<1xf32>, tensor<1xf32>) -> tensor<2x1xf32> func.return %0 : tensor<2x1xf32> // CHECK: %[[VAL_0:.*]] = arith.constant dense<[2, 1]> : tensor<2xi32> // CHECK: %[[CONCAT:.*]] = "tfl.concatenation"(%arg0, %arg1) <{axis = 0 : i32, fused_activation_function = "NONE"}> : (tensor<1xf32>, tensor<1xf32>) -> tensor<2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 1.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/transforms/legalize_tf_patterns.td
: Constraint<CPred<"$0.getType().isa<RankedTensorType>()">>; // This pattern converts TensorFlow axis format to HLO axis format which // doesn't wrap around like TensorFlow and is always positive. For this // conversion, use the first input to get inputs rank. Other inputs need not be // ranked. // Defining op for `axis` is TensorFlow constant op in the pattern as during
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon May 06 18:46:23 UTC 2024 - 34.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/ir/FakeQuantSupport.cc
} SmallVector<double, 4> scales; SmallVector<int64_t, 4> zeroPoints; scales.reserve(axisSize); zeroPoints.reserve(axisSize); for (size_t axis = 0; axis != axisSize; ++axis) { double rmin = rmins[axis]; double rmax = rmaxs[axis]; if (std::fabs(rmax - rmin) < std::numeric_limits<double>::epsilon()) { scales.push_back(1.0); zeroPoints.push_back(qmin); continue; }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 21 11:52:27 UTC 2024 - 7.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/tests/e2e/simple-graph.mlir
%2 = "tfl.add"(%arg0, %arg3) {fused_activation_function = "RELU6"} : (tensor<1xf32>, tensor<1xf32>) -> tensor<1xf32> %3 = "tfl.pack"(%1, %2) {axis = 0 : i32, values_count = 2 : i32} : (tensor<1xf32>, tensor<1xf32>) -> tensor<2x1xf32> func.return %3 : tensor<2x1xf32> } // CHECK: %[[CST:.*]] = arith.constant dense<1> : tensor<4xi32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 1.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/fuse-tftext.mlir
%178 = "tf.Pack"(%7, %177) {axis = 0 : i64, device = ""} : (tensor<i32>, tensor<i32>) -> tensor<2xi32> %179 = "tf.Tile"(%115, %178) {device = ""} : (tensor<?x1xi64>, tensor<2xi32>) -> tensor<?x?xi64> %180 = "tf.Mul"(%177, %118) {device = ""} : (tensor<i32>, tensor<i32>) -> tensor<i32> %181 = "tf.Pack"(%180) {axis = 0 : i64, device = ""} : (tensor<i32>) -> tensor<1xi32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 460.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/passes/bridge/convert_tf_quant_types_test.cc
func.func @main(%arg0: tensor<3x3x!tf_type.qint8>, %arg1: tensor<3x3x!tf_type.qint8>) -> tensor<6x3x!tf_type.qint8> { %axis = "tf.Const"() { value = dense<0> : tensor<i64> } : () -> tensor<i64> %1 = "tf.ConcatV2"(%arg0, %arg1, %axis) : (tensor<3x3x!tf_type.qint8>, tensor<3x3x!tf_type.qint8>, tensor<i64>) -> tensor<6x3x!tf_type.qint8> func.return %1 : tensor<6x3x!tf_type.qint8> } })";
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 05 09:05:02 UTC 2024 - 4.2K bytes - Viewed (0)