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Results 51 - 60 of 70 for conv_3d (0.21 sec)
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test/typeparam/issue49027.dir/main.go
if x != s { panic(fmt.Sprintf("got %s wanted %s", x, s)) } y, ok := a.Conv2(s) if !ok { panic("conversion failed") } if y != s { panic(fmt.Sprintf("got %s wanted %s", y, s)) } z := a.Conv3(s) if z != s { panic(fmt.Sprintf("got %s wanted %s", z, s)) } w := a.Conv4(a.Mystring(s)) if w != a.Mystring(s) { panic(fmt.Sprintf("got %s wanted %s", w, s)) }
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Thu Mar 24 02:14:15 UTC 2022 - 617 bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/end2end/conv_2d_nchw.pbtxt
} } attr { key: "_class" value { list { s: "loc:@conv_net_2d/conv_2d_0/w" } } } } node { name: "conv_net_2d_1/conv_2d_0/convolution" op: "Conv2D" input: "input" input: "conv_net_2d/conv_2d_0/w/read" attr { key: "T" value { type: DT_FLOAT } } attr { key: "data_format" value { s: "NCHW" }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Dec 03 03:26:13 UTC 2021 - 3.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/optimize.mlir
%6 = "tf.Cast"(%5) {Truncate = false} : (tensor<1x100x100x1xi8>) -> tensor<1x100x100x1xf32> %7 = "tf.Sub"(%6, %cst_4) : (tensor<1x100x100x1xf32>, tensor<f32>) -> tensor<1x100x100x1xf32> %8 = "tf.Conv2D"(%7, %cst_3) {dilations = [1, 1, 1, 1], padding = "VALID", strides = [1, 1, 1, 1]} : (tensor<1x100x100x1xf32>, tensor<3x3x1x1xf32>) -> tensor<1x98x98x1xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 8.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/hardwares/gpu_hardware.cc
return false; } return true; } }; 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;
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/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/quantization/tensorflow/passes/lift_quantizable_spots_as_functions_drq.cc
if ((quantization_method_ == tensorflow::quantization::QuantizationMethod:: METHOD_DYNAMIC_RANGE_INT8) && (function_name.contains("batch_matmul") || function_name.contains("conv3d"))) { call_op->removeAttr(kQuantTraitAttrName); } // TODO(b/270906404): Support weight-only gather for uniform quantized opset // in PTQ mode if (target_opset_ == OpSet::UNIFORM_QUANTIZED &&
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 8.5K 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) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/prepare_quantize_ptq_per_channel.mlir
%1 = "quantfork.stats"(%arg0) {layerStats = dense<[1.27501142, 149.824783]> : tensor<2xf32>} : (tensor<1x3x4x3xf32>) -> tensor<1x3x4x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 01 10:21:29 UTC 2023 - 4.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/debuginfo/v1_1.0_224_frozen.wrong_attr.stack.part.pbtxt.debug
key: "MobilenetV1/MobilenetV1/Conv2d_0/BatchNorm/FusedBatchNorm@" value { file_line_cols { file_index: 5 line: 362 } } } traces { key: "MobilenetV1/MobilenetV1/Conv2d_0/Conv2D@" value { file_line_cols { file_index: 2 line: 27 } file_line_cols { file_index: 3 line: 28 } file_line_cols { file_index: 4
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Dec 11 15:36:55 UTC 2019 - 3.9K bytes - Viewed (0)