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tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization.td
(ins "bool":$sign, "int":$bit_width) >, ]; } def AffineQuantizedOpInterface : OpInterface< "AffineQuantizedOpInterface"> { let description = [{ Interface for affine quantized ops (conv2d, fully_connected, etc.) }]; let methods = [ InterfaceMethod< [{Returns the affine operand index.}], "int", "GetAffineOperandIndex", (ins), [{}], [{return 1;}]>, InterfaceMethod<
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 05 07:39:40 UTC 2024 - 8.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/attrs_and_constraints.cc
.getRank(); // To quantize rhs per-channel, we currently only consider the case where // `stablehlo.dot_general` is legalizable to `tfl.fully_connected`. const bool is_per_axis_quantizable = IsDotGeneralFullyConnected(dot_general_op).value(); if (!is_per_axis_quantizable) return std::nullopt; return filter_rank - 1; }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 6.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/hardwares/gpu_hardware.cc
} }; std::unique_ptr<TargetHardwareOperation> CreateConcatOp() { return std::make_unique<GpuConcatOp>(); } // Currently used for these ops: // tfl.conv_2d / tfl.depthwise_conv_2d / tfl.fully_connected class GpuConvOp : public TargetHardwareOperation { double GetOpCost(mlir::Operation* op) const override { int64_t arithmetic_count; if (ArithmeticCountUtilHelper::GetArithmeticCountForConvAndFullyconnectedOp(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 06 03:08:33 UTC 2023 - 7.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-quantize-dynamic-range.mlir
%w = arith.constant dense<127.0> : tensor<512x12xf32> %b = arith.constant dense<0.0> : tensor<512xf32> %fc = "tfl.fully_connected"(%0, %w, %b) {fused_activation_function = "NONE", keep_num_dims = false, weights_format = "DEFAULT"} : (tensor<1x224x224x3xf32>, tensor<512x12xf32>, tensor<512xf32>) -> tensor<1x112x112x512xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 38.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/canonicalize.mlir
%0 = "tfl.pseudo_const"() {value = dense<0.0> : tensor<40xf32>} : () -> tensor<40xf32> %1 = "tfl.fully_connected"(%arg0, %arg1, %0) {fused_activation_function = "NONE", keep_num_dims = false, weights_format = "DEFAULT"} : (tensor<1x37xf32>, tensor<40x37xf32>, tensor<40xf32>) -> tensor<1x40xf32> // CHECK: "tfl.fully_connected" // CHECK-SAME: (tensor<1x37xf32>, tensor<40x37xf32>, none) -> tensor<1x40xf32> func.return %1 : tensor<1x40xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 20.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/uniform_quantized_stablehlo_to_tfl_pass.cc
// filter value from [i, o] -> [o, i]. This is because we assume `[i, o]` // format for `stablehlo.dot_general` (i.e. contracting dimension == 1) // whereas `tfl.fully_connected` accepts an OI format. TFL::QConstOp CreateTransposedTflConstOpForFilter( stablehlo::ConstantOp filter_constant_op, PatternRewriter& rewriter, bool is_per_channel) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 22 09:00:19 UTC 2024 - 99.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/test_schema.fbs
} // An implementation of TensorFlow fully_connected (a.k.a Dense) layer. table FullyConnectedOptions { // Parameters for FullyConnected version 1 or above. fused_activation_function:ActivationFunctionType; // Parameters for FullyConnected version 2 or above. weights_format:FullyConnectedOptionsWeightsFormat = DEFAULT; // Parameters for FullyConnected version 5 or above.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 19 19:46:06 UTC 2021 - 26.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/optimize.cc
// Remove Reshape before FullyConnected when `keep_num_dims=false` and Reshape // does not alter the last dimension as FullyConnected will collapse all other // dimensions into a single dimension. For example, // // %shape = arith.constant dense<[1, 128, 64]> : tensor<3xi32> // %reshape = tfl.reshape(%input, %shape) // %input: tensor<128x64xf32> // %fc = tfl.fully_connected(%reshape, %filter, %bias)
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/quantization/common/attrs_and_constraints.h
// is quantized. bool IsHybridQuantizedOp(Operation* op); // Returns whether a given `stablehlo.dot_general` can be legalizable to // `tfl.fully_connected`. absl::StatusOr<bool> IsDotGeneralFullyConnected( ::mlir::stablehlo::DotGeneralOp dot_general_op); // Returns the quantization dimension for a given `stablehlo.dot_general` op,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 9.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/schema/schema_v3b.fbs
} // An implementation of TensorFlow fully_connected (a.k.a Dense) layer. table FullyConnectedOptions { // Parameters for FullyConnected version 1 or above. fused_activation_function:ActivationFunctionType; // Parameters for FullyConnected version 2 or above. weights_format:FullyConnectedOptionsWeightsFormat = DEFAULT; // Parameters for FullyConnected version 5 or above.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 28 14:28:27 UTC 2024 - 30K bytes - Viewed (0)