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Results 11 - 20 of 48 for fully_connected (0.48 sec)
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tensorflow/compiler/mlir/lite/tests/quantize-dynamic-range.mlir
func.func @QuantizeFullyConnected(%arg0: tensor<1x224x224x3xf32>) -> tensor<1x112x112x512xf32> { %w = arith.constant dense<127.0> : tensor<512x12xf32> %b = arith.constant dense<0.0> : tensor<512xf32> %fc = "tfl.fully_connected"(%arg0, %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 23 21:09:00 UTC 2024 - 23.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/quantize.mlir
// RUN: tf-opt %s -tfl-prepare-quantize -tfl-quantize | FileCheck %s // RUN: tf-opt %s -tfl-quantize="legacy-quantize=true" | FileCheck --check-prefix=LEGACY %s // RUN: tf-opt %s -tfl-prepare-quantize -tfl-quantize="ops-blocklist=tfl.fully_connected,tfl.softmax locs-blocklist=Block,NullBlock" | FileCheck --check-prefix=BLOCK %s // CHECK-LABEL: QuantizeFloatConst func.func @QuantizeFloatConst() -> tensor<2x2x!quant.uniform<u8:f32, 7.8431372549019615E-4:128>> {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 28 23:10:13 UTC 2024 - 39.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/utils/arithmetic_count_util.h
return false; } total_count += input_type.getNumElements(); } *count = total_count; return true; } // For conv2d/depthwise_conv/fully_connected ops. // This algorithm actually comes from TOCO tooling_util.cc static bool GetArithmeticCountForConvAndFullyconnectedOp(mlir::Operation* op, int64_t* count) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 3.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/uniform-quantized-stablehlo-to-tfl.mlir
// CHECK: return %[[FULLY_CONNECTED]] // ----- // Tests that when the weight tensor for `stablehlo.dot_general` has a // `stablehlo.constant` -> `stablehlo.transpose` pattern, the // `stablehlo.constant` is directly transformed to `tfl.pseudo_qconst`, which // becomes the rhs of `tfl.fully_connected`. This is because // `tfl.fully_connected` accepts a [o, i] format for rhs, which
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 17:10:32 UTC 2024 - 106.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/optimize_batch_matmul.cc
OptimizeBatchMatmulPass() = default; OptimizeBatchMatmulPass(const OptimizeBatchMatmulPass &) {} void runOnOperation() override; }; // Converts batch_matmul operation to fully_connected if rhs is a // constant tensor with rank 2 struct ConvertBatchMatMulOp2FullyConnectedOp : public OpRewritePattern<TFL::BatchMatMulOp> { using OpRewritePattern<TFL::BatchMatMulOp>::OpRewritePattern;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 9.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/post-quantize.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 19.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/tests/fold-constants-to-subgraph.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 10.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-quantize-post-training-16bits.mlir
%2 = "tfl.pseudo_const"() {value = dense<[[0.1, 0.1, 0.1]]> : tensor<1x3xf32>} : () -> tensor<1x3xf32> %3 = "tfl.pseudo_const"() {value = dense<[0.1]> : tensor<1xf32>} : () -> tensor<1xf32> %4 = "tfl.fully_connected"(%1, %2, %3) {asymmetric_quantize_inputs = false, fused_activation_function = "NONE", keep_num_dims = false, weights_format = "DEFAULT"} : (tensor<1x3xf32>, tensor<1x3xf32>, tensor<1xf32>) -> tensor<1x1xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 26.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/const-fold.mlir
%cst_weights = arith.constant dense<[[5.0, 7.0], [11.0, 13.0], [17.0, 19.0]]> : tensor<3x2xf32> %cst_bias = arith.constant dense<[23.0, 29.0, 31.0]> : tensor<3xf32> %0 = "tfl.fully_connected" (%cst_input, %cst_weights, %cst_bias) {fused_activation_function = "NONE", keep_num_dims = false, weights_format = "DEFAULT"} : (tensor<2xf32>, tensor<3x2xf32>, tensor<3xf32>) -> tensor<3xf32> func.return %0 : tensor<3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 45.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/decompose-hybrid-quantization.mlir
// CHECK-DAG: %[[VAL3:.+]] = "tfl.dequantize"(%[[VAL1]]) : (tensor<36x!quant.uniform<i32:f32, 1.000000e+00>>) // CHECK: %[[VAL4:.+]] = "tfl.fully_connected"(%arg0, %[[VAL2]], %[[VAL3]]) <{fused_activation_function = "NONE", keep_num_dims = false, weights_format = "DEFAULT"}> // CHECK: return %[[VAL4]]
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 13.1K bytes - Viewed (0)