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Results 141 - 150 of 173 for conv_3d (0.14 sec)
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tensorflow/compiler/mlir/tfr/examples/mnist/ops_defs.py
derived_attrs=['T: {float, int8}'], outputs=['o: T']) def _composite_conv_add_relu(input_, filter_, bias, stride_w, stride_h, dilation_w, dilation_h, padding, act): res = tf.raw_ops.Conv2D( input=input_, filter=filter_, strides=[1, stride_w, stride_h, 1], dilations=[1, dilation_w, dilation_h, 1], padding=padding) res = tf.raw_ops.Add(x=res, y=bias) if act == 'RELU':
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Aug 31 20:23:51 UTC 2023 - 6.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/tests/legalize-tf-prefer-tf2xla.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 15:32:52 UTC 2024 - 15.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/tf_to_corert/tf_to_corert_pipeline.mlir
%outputs_6, %control_7 = tf_executor.island wraps "tf.Const"() {device = "", value = dense<[-1, 16384]> : tensor<2xi32>} : () -> tensor<2xi32> %outputs_8, %control_9 = tf_executor.island wraps "tf.Conv2D"(%arg0, %outputs_0) {data_format = "NHWC", device = "", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 2, 2, 1], use_cudnn_on_gpu = true} : (tensor<16x224x224x3xf32>, tensor<*xf32>) -> tensor<16x112x112x?xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 08 00:18:59 UTC 2024 - 7.7K bytes - Viewed (0) -
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/quantization/tensorflow/tests/prepare_quantize_ptq.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 - 9.1K 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/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) -
tensorflow/compiler/mlir/lite/stablehlo/tests/legalize_hlo.mlir
// CHECK: %[[VAL_9:.*]] = "tf.Transpose"(%[[VAL_7]], %[[VAL_8]]) : (tensor<1x256x256x1xbf16>, tensor<4xi64>) -> tensor<1x1x256x256xbf16>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 29 07:26:59 UTC 2024 - 340.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/python/integration_test/quantize_model_test.py
), ) quantization.quantize_saved_model( self._input_saved_model_path, self._output_saved_model_path, config, ) expected_outputs = model.conv2d(input_data) root = load.load(self._output_saved_model_path) self.assertCountEqual(root.signatures.keys(), {'serving_default'}) new_outputs = root.signatures['serving_default'](
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 06:31:57 UTC 2024 - 51.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/quantization_options.proto
// NEXT ID: 7 message UnitWiseQuantizationSpec { // Quantization unit granularity. // NEXT ID: 4 message QuantizationUnit { // Type of the op, ex: Conv2D, MatMul, Einsum... The node_name field can // be omitted if it is intended to match all nodes with this type. string op_type = 1; // Name of the node. This field accepts re2 regex format. If the node name
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 19 06:31:19 UTC 2024 - 9.2K bytes - Viewed (0)