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Results 1 - 10 of 108 for Quantized (0.24 sec)
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tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization.td
string name = n; string asTraitArgsStr = !interleave(params, ", ") # !if(signed, ", true", ", false"); } // Uniform quantized types. Two integers "smantissa" and "sexp" are used to // express the Mantissa and Exponent components of the floating-point scale so // the scale of the quantized type is "smantissa * 10 ^ sexp". class UInt8UniformQuantizedType<int zero_pt, int smantissa, int sexp> : QuantizedType<"Uniform",
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/uniform_quantized_types.h
// Returns true iff `type` is a uniform quantized type whose storage type is // 32-bit integer and expressed type is f32. bool IsI32F32UniformQuantizedType(Type type); // Returns true iff `type` is a uniform quantized per-axis (per-channel) type // whose storage type is 32-bit integer and expressed type is f32. bool IsI32F32UniformQuantizedPerAxisType(Type type); // Determines whether the storage type of a quantized type is supported by
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 5.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/uniform_quantized_types.cc
<< quantized_per_axis_type << ".\n"); return false; } return true; } // Determines whether the storage type of a quantized type is supported by // `tfl.quantize` or `tfl.dequantize` ops. ui8, i8 and i16 are supported. bool IsSupportedByTfliteQuantizeOrDequantizeOps(IntegerType storage_type) { if (storage_type.getWidth() == 8 ||
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 8.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/quantize/quantize.mlir
return %7 : tensor<1x3xf32> } // Test that the inputs and output of the tf.XlaCallModule op has been replaced // by quantized types, and the corresponding quantfork.dcast ops that turned // those quantized types back to float types are removed. // CHECK: %[[CONST_0:.+]] = stablehlo.constant dense<1.000000e+00> : tensor<4x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 18 01:38:40 UTC 2024 - 6.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/passes/quantize_composite_functions.cc
}; void QuantizeCompositeFunctionsPass::runOnOperation() { MLIRContext& ctx = getContext(); PassManager pm(&ctx); // Intermediate output from QuantizePass will have quantized ops // (XlaCallModuleOps) with quantized input and output types, which are not // allowed in the TF dialect. pm.enableVerifier(false); PrepareQuantizePassOptions options; options.enable_per_channel_quantized_weight_ =
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 03 02:59:01 UTC 2024 - 4.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/quantization_options.proto
METHOD_NO_QUANTIZE = 1; // Static range quantization. Quantized tensor values' ranges are statically // determined. The activation and weight are quantized to INT8 while bias is // quantized to INT32. METHOD_STATIC_RANGE_INT8 = 2; // Dynamic range quantization. Quantized tensor values' ranges are // determined in the graph executions. The weights are quantized during // conversion. METHOD_DYNAMIC_RANGE_INT8 = 3;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 19 06:31:19 UTC 2024 - 9.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/cc/report.cc
return result; } else { return std::nullopt; } } // Populates quantized ops from `module_op` to `results`. After going through // the quantization passes, quantized ops are represented as `func::CallOp` with // a callee's prefix of `quantized_`. void PopulateQuantizedResults(ModuleOp module_op, QuantizationResults& results) {
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/stablehlo/transforms/passes.td
def ComposeUniformQuantizedTypePass : Pass<"compose-uniform-quantized-type", "ModuleOp"> { let summary = "Compose uniform quantized types in StableHLO."; let constructor = "mlir::odml::CreateComposeUniformQuantizedTypePass()"; let description = [{ Identifies uniform quantization patterns and composes them to uniform quantized types. This pass targets a specific set of models that are quantized from the framework level, which produces "decomposed"
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 21:59:06 UTC 2024 - 5.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/components/post_calibration_component.mlir
// RUN: stablehlo-quant-opt %s -stablehlo-test-post-calibration-component='unpack-quantized-types=false' \ // RUN: -split-input-file | FileCheck %s --check-prefix=CHECK-NO-UNPACK // Tests that a simple dot_general (lifted as a function) with CustomAggregators // around it is quantized. The resulting graph has quantized types unpacked into // int ops. func.func @main(%arg0: tensor<1x1024xf32>) -> tensor<1x3xf32> {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 01:09:50 UTC 2024 - 6.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/ir/ConvertConst.cc
/// quantized and the operand type is quantizable. LogicalResult QuantizedConstRewrite::matchAndRewrite( QuantizeCastOp qbarrier, PatternRewriter &rewriter) const { Attribute value; // Is the operand a constant? if (!matchPattern(qbarrier.getArg(), m_Constant(&value))) { return failure(); } // Does the qbarrier convert to a quantized type. This will not be true
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 4.4K bytes - Viewed (0)