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Results 91 - 100 of 173 for conv_3d (0.28 sec)
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tensorflow/compiler/mlir/quantization/tensorflow/tests/convert_tpu_model_to_cpu.mlir
%4 = "tf.Transpose"(%3, %cst_1) {_tpu_replicate = "cluster", device = ""} : (tensor<1x3x3x4xbf16>, tensor<4xi32>) -> tensor<1x3x4x3xbf16>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 4.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/add_dump_tensor_op.mlir
// IntPerLayer-DAG: "tf.DumpTensor"(%[[output0_unquantized]]) <{enabled = true, file_name = "unquantized_tensor_data.pb", func_name = "multiple_conv2d", log_dir_path = "/tmp/dumps/composite_conv2d_with_bias_and_relu6_fn_2", node_name = "Conv2D"}>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 22 22:55:22 UTC 2024 - 37.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/tensorflow/tests/tf_to_quant_4bit.mlir
%fq = "tf.FakeQuantWithMinMaxVars"(%in, %mini, %maxi) {num_bits = 3, narrow_range = false} : (tensor<3x3x3x16xf32>, tensor<f32>, tensor<f32>) -> tensor<3x3x3x16xf32> %rst = "tf.Conv2D"(%arg, %fq) {T = "tfdtype$DT_FLOAT", data_format = "NHWC", dilations = [1, 2, 3, 1], padding = "SAME", strides = [1, 4, 5, 1]} : (tensor<256x32x32x3xf32>, tensor<3x3x3x16xf32>) -> tensor<256x8x7x16xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 9.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/python/integration_test/quantize_model_test.py
] ) def conv3d(self, input_tensor: core.Tensor) -> Mapping[str, core.Tensor]: """Performs a 3D convolution operation. Args: input_tensor: Input tensor to perform convolution on. Returns: A map of: output key -> output result. """ out = nn_ops.conv3d( input_tensor, self.filters,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 03:36:50 UTC 2024 - 235.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/layout_optimization_layout_assignment_gpu_cc_60.mlir
// cuDNN prefers NCHW data format for spatial convolutions in f16 before // compute capability 7.0 (NVIDIA Tensor Cores). // CHECK: "tf.Conv2D"(%[[INPUT_TRANSPOSE:[0-9]*]], %arg1) // CHECK-SAME: data_format = "NCHW" %0 = "tf.Conv2D"(%input, %filter) { data_format = "NHWC", padding = "VALID", strides = [1, 1, 1, 1]
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 21 08:41:18 UTC 2022 - 5.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/debuginfo/v1_1.0_224_frozen.wrong_attr.line.part.pbtxt
} } attr { key: "_class" value { list { s: "loc:@MobilenetV1/Conv2d_0/weights" } } } } node { name: "MobilenetV1/MobilenetV1/Conv2d_0/Conv2D" op: "Conv2D" input: "input" input: "MobilenetV1/Conv2d_0/weights/read" attr { key: "T" value { type: DT_FLOAT } } attr { key: "data_format" value {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jul 27 18:59:05 UTC 2023 - 16.2K bytes - Viewed (0) -
tensorflow/compiler/jit/tests/keras_imagenet_main_graph_mode.golden_summary
ReadVariableOp 2 VarHandleOp 435 _Retval 2 cluster 0 size 2178 Add 17 AddN 72 ArgMax 1 AssignAddVariableOp 1 AssignSubVariableOp 106 BiasAdd 1 BiasAddGrad 1 Cast 3 Const 357 Conv2D 53 Conv2DBackpropFilter 53 Conv2DBackpropInput 52 DivNoNan 1 Equal 1 FusedBatchNorm 53 FusedBatchNormGrad 53 Identity 2 MatMul 3 MaxPool 1 MaxPoolGrad 1 Mean 1 Mul 164 Pad 1
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 06 10:38:14 UTC 2023 - 740 bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/optimize.mlir
// CHECK: %0 = "tfl.conv_2d"(%arg0, %arg1, %cst) } // CHECK-LABEL: fuse4DAddIntoConv2d func.func @fuse4DAddIntoConv2d(%arg0: tensor<256x32x32x3xf32>, %arg1: tensor<2x3x3x3xf32>) -> tensor<256x32x32x2xf32> { %cst = arith.constant dense<[[[[1.0, 2.0]]]]> : tensor<1x1x1x2xf32> %cst_0 = arith.constant dense<[1.0, 2.0]> : tensor<2xf32> %0 = "tfl.conv_2d"(%arg0, %arg1, %cst_0) { dilation_h_factor = 1 : i32,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 16 20:31:41 UTC 2024 - 284.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/insert_quantized_functions_drq.mlir
// CHECK-NOT: func private @internal_matmul_fn // CHECK: func private @quantized_matmul_fn // CHECK-SAME: tf_quant.quantized_ops = ["MatMul"] // CHECK: func private @quantized_conv2d_fn // CHECK-SAME: tf_quant.quantized_ops = ["Conv2D"] // CHECK: func private @quantized_depthwise_conv2d_fn // CHECK-SAME: tf_quant.quantized_ops = ["DepthwiseConv2D"] // UQ-CHECK: func private @quantized_conv2d_fn // UQ-CHECK: func private @quantized_depthwise_conv2d_fn
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Dec 01 12:06:54 UTC 2022 - 1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/python/integration_test/quantize_model_test_base.py
save_options = None if has_func_alias: save_options = tensorflow.saved_model.SaveOptions( function_aliases={FUNC_ALIAS: model.conv2d} ) saved_model_save.save( model, saved_model_path, signatures=model.conv2d.get_concrete_function( tensor_spec.TensorSpec( shape=input_shape, dtype=dtypes.float32, name='input_tensor' )
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 06:31:57 UTC 2024 - 18.2K bytes - Viewed (0)