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Results 101 - 110 of 202 for conv3d (0.33 sec)
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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/quantization/tensorflow/tests/quantize_composite_functions_weight_only.mlir
%conv = "tf.Conv2D"(%arg0, %arg1) {attr_map = "0:strides,1:use_cudnn_on_gpu,2:padding,3:explicit_paddings,4:dilations", data_format = "NHWC", device = "", dilations = [1, 2, 2, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 2, 1], use_cudnn_on_gpu = true} : (tensor<1x2x2x3xf32>, tensor<2x3x3x2xf32>) -> tensor<*xf32> return %conv : tensor<*xf32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 11.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/python/integration_test/quantize_model_test_base.py
# One pure conv out = nn_ops.conv2d( out, self.conv_filters, strides=(1, 1, 2, 1), dilations=(1, 1, 1, 1), padding='SAME', data_format='NHWC', ) # One fakequant attached conv if is_qat_model: out = array_ops.fake_quant_with_min_max_args(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 21 08:51:46 UTC 2024 - 51.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/utils/arithmetic_count_util.h
if (!input_type || !input_type.hasStaticShape()) { 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,
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/quantization/tensorflow/passes/quantized_function_library_uniform_quantized_drq.mlir
%input : tensor<*xf32>, %weight : tensor<*x!tf_type.qint8>, %weight_scale : tensor<*xf32>, %weight_zp : tensor<*xi32>) -> tensor<*xf32> attributes {tf_quant.quantized_ops = ["Conv2D"]} { %out = "tf.UniformQuantizedConvolutionHybrid"(%input, %weight, %weight_scale, %weight_zp) { Tlhs = "tfdtype$DT_FLOAT", Trhs = "tfdtype$DT_QINT8",
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Dec 01 12:06:54 UTC 2022 - 3.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-quantize.mlir
%conv1 = "tfl.conv_2d"(%1, %2, %cst) {dilation_h_factor = 1 : i32, dilation_w_factor = 1 : i32, fused_activation_function = "NONE", padding = "SAME", stride_h = 2 : i32, stride_w = 2 : i32} : (tensor<1x224x224x3xf32>, tensor<32x3x3x3xf32>, tensor<32xf32>) -> tensor<1x112x112x32xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 67.5K bytes - Viewed (0) -
src/cmd/go/testdata/vcstest/git/retract-pseudo.txt
handle git env GIT_AUTHOR_NAME='Jay Conrod' env GIT_AUTHOR_EMAIL='******@****.***' env GIT_COMMITTER_NAME=$GIT_AUTHOR_NAME env GIT_COMMITTER_EMAIL=$GIT_AUTHOR_EMAIL at 2020-10-09T13:37:47-04:00 git init git add go.mod p.go git commit -m 'create module retract-pseudo' git branch -m main git tag v1.0.0 git mv p.go q.go git commit -m 'trivial change' git show-ref --tags --heads cmp stdout .git-refs
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Tue Oct 25 15:36:24 UTC 2022 - 651 bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/tests/target-annotation.mlir
func.func @testConv(%arg0: tensor<256x32x32x3xf32>, %arg1: tensor<16x3x3x3xf32>, %arg2: tensor<16xf32>) -> tensor<256x30x30x16xf32> { // CHECK: tac.device = "GPU", tac.inference_type = "FLOAT"
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 19 19:32:06 UTC 2023 - 6.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/quantize-numeric-verify.mlir
// DEBUG: %[[act:.*]] = "tfl.dequantize"(%arg0) : (tensor<1x224x224x3x!quant.uniform<u8:f32, 7.812500e-03:128>>) -> tensor<1x224x224x3xf32> // DEBUG: %[[f_conv:.*]] = "tfl.conv_2d"(%[[act]], %[[wt]], %[[bias]]) // DEBUG: %[[q_conv:.*]] = "tfl.conv_2d" // DEBUG: "tfl.NumericVerify"(%[[q_conv]], %[[f_conv]]) <{log_if_failed = true, tolerance = 5.000000e+00 : f32}>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 15.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/fake_quant_e2e_flow.mlir
%1 = "tf.FakeQuantWithMinMaxArgs"(%arg0) {device = "", max = 2.000000e-01 : f32, min = -1.000000e-01 : f32, narrow_range = false, num_bits = 8 : i64} : (tensor<1x3x4x3xf32>) -> tensor<*xf32> %2 = "tf.Conv2D"(%1, %0) {data_format = "NHWC", device = "", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 2, 1], use_cudnn_on_gpu = true} : (tensor<*xf32>, tensor<*xf32>) -> tensor<*xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 3.5K bytes - Viewed (0)