- Sort Score
- Result 10 results
- Languages All
Results 61 - 67 of 67 for conv_2d (0.32 sec)
-
tensorflow/compiler/mlir/quantization/tensorflow/passes/quantized_function_library_uniform_quantized.mlir
// func.func func_name_${key1}_fn (...) { // ...${key2}... // } // ``` // The above template with generate two functions by substituting `key1` and // `key2` with given values. module { for main_op in ["Conv2D", "DepthwiseConv2D", "MatMul"] { parameters[ {"quantized_ops": ["${main_op}", "BiasAdd"], "act_func": "internal_requantize_no_activation_fn", "output_type": "!tf_type.qint8"},
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Aug 29 01:13:58 UTC 2023 - 19.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tf_tfl_passes.cc
// Canonicalization includes const folding, which is utilized here to optimize // away ops that can't get constant folded after PrepareTF pass. For example, // tf.Conv2D is split into tf.Transpose and tfl.Conv2D. pass_manager->addNestedPass<mlir::func::FuncOp>( mlir::createCanonicalizerPass()); pass_manager->addNestedPass<mlir::func::FuncOp>(mlir::createCSEPass());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 18:45:51 UTC 2024 - 25.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/legalize_tf.cc
dilation_width_factor = rewriter.getI32IntegerAttr(1); } StringAttr padding; if (!TFPaddingIsSameOrValid(op, &padding)) return failure(); // TensorFlow Conv3D has no bias, optimization patterns will fuse Conv3D // with other ops can fill the bias. Value none = rewriter.create<TFL::NoValueOp>( op->getLoc(), rewriter.getNoneType(), rewriter.getUnitAttr());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon May 20 20:06:54 UTC 2024 - 45.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/insert_calibration_statistics_saver.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 01:09:50 UTC 2024 - 24.3K bytes - Viewed (0) -
src/database/sql/convert_test.go
rows.raw = rows.raw[:0] test(tt.name, tt.in, tt.want) } }) // The numbers below are only valid for 64-bit interface word sizes, // and gc. With 32-bit words there are more convT2E allocs, and // with gccgo, only pointers currently go in interface data. // So only care on amd64 gc for now. measureAllocs := false switch runtime.GOARCH { case "amd64", "arm64":
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Wed Apr 10 20:23:22 UTC 2024 - 17K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfr/ir/tfr_ops.cc
// TFR_ConstantTensorOp ( // ConstantOp (ConstAttr<F32Attr (in_scale[0] * in_scale[1] / // out_scale)) // ) // Currently, all decompositions using this pattern (Conv2D, FC) have the // following preconditions: // * out_scale: float scalar attribute // * in_scale[0] (input scale): float scalar, given by tf.Const -> tfr.cast // * in_scale[1] (filter scale): float scalar/vector
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Nov 21 16:55:41 UTC 2023 - 38.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/passes/bridge/convert_tf_quant_to_mhlo_int_test.cc
quantization_axis = -1 : i64, quantization_min_val = -128 : i64, quantization_max_val = 127 : i64 } : ( tensor<3x3x10x20x!tf_type.qint8>, tensor<f32>, tensor<i32> ) -> tensor<3x3x10x20xf32> %0 = "tf.Conv2D"(%input, %filter_new) { Tin = "tfdtype$DT_FLOAT", Tout = "tfdtype$DT_FLOAT", attr_map = "", batch_group_count = 1 : i64, explicit_padding = [], feature_group_count = 1 : i64, lhs_dilation = [1, 1],
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Apr 03 01:03:21 UTC 2024 - 35.8K bytes - Viewed (0)