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Results 21 - 30 of 202 for conv3d (0.23 sec)
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tensorflow/compiler/mlir/lite/tests/end2end/conv_2d.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: "NHWC" }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jun 28 06:29:38 UTC 2019 - 3.7K bytes - Viewed (0) -
tensorflow/compiler/jit/mark_for_compilation_pass.cc
"BiasAddV1", "Bincount", "Bucketize", "Case", "CheckNumerics", "Cholesky", "ControlTrigger", "Conv", "Conv2D", "Conv2DBackpropFilter", "Conv2DBackpropInput", "Conv3D", "Conv3DBackpropFilterV2", "Conv3DBackpropInputV2", "Cross", "Cumprod", "Cumsum", "CumulativeLogsumexp",
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 21 12:19:41 UTC 2024 - 85.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/dilated-conv.mlir
// CHECK-NEXT: [[CONV:%.*]] = "tf.Conv2D"([[INPUT]], [[FILTER]]) <{dilations = [1, 2, 2, 1], padding = "SAME", strides = [1, 1, 1, 1]}> : (tensor<1x128x128x3xf32>, tensor<5x5x3x8xf32>) -> tensor<1x128x128x8xf32> // CHECK-NEXT: [[RESULT:%.*]] = "tf.BiasAdd"([[CONV]], [[BIAS]]) : (tensor<1x128x128x8xf32>, tensor<8xf32>) -> tensor<1x128x128x8xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 44.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-tf-with-allowing-bf16-and-f16-type-legalization.mlir
%0 = "tf.Conv2D"(%arg0, %arg1) {T = "tfdtype$DT_FLOAT", data_format = "NHWC", dilations = [1, 2, 3, 1], padding = "SAME", strides = [1, 4, 5, 1]} : (tensor<256x32x32x3xbf16>, tensor<3x3x3x16xbf16>) -> tensor<256x8x7x16xbf16> func.return %0 : tensor<256x8x7x16xbf16> // CHECK: "tfl.conv_2d" } // CHECK-LABEL: fused_batch_norm_v3_bf16
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 26 23:53:32 UTC 2022 - 2.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/optimize_functional_ops.mlir
// Verify unused if with functions without side-effects is removed. // CHECK-LABEL: main func.func @main(%arg0: tensor<3x15x14x3xf32>) -> tensor<3x15x14x8xf32> attributes {tf.entry_function = {inputs = "input", outputs = "Conv2D"}} { %cst = arith.constant dense<[0, 1, 2, 3]> : tensor<4xi32> %cst_0 = arith.constant dense<1.000000e+00> : tensor<f32> %cst_1 = arith.constant dense<0.000000e+00> : tensor<8xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Mar 30 10:34:48 UTC 2022 - 8.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/end2end/fake_quant_per_channel.pbtxt
key: "narrow_range" value { b: true } } attr { key: "num_bits" value { i: 8 } } } node { name: "BoxPredictor_4/ClassPredictor/Conv2D" op: "Conv2D" input: "input" input: "BoxPredictor_4/ClassPredictor/weights_quant/FakeQuantWithMinMaxVarsPerChannel" attr { key: "T" value { type: DT_FLOAT } } attr {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 18.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-tf.mlir
// Unsupported data format %1 = "tf.Conv2D"(%arg2, %arg1) {T = "tfdtype$DT_FLOAT", data_format = "NCHW", dilations = [1, 1, 1, 1], padding = "SAME", strides = [1, 1, 1, 1]} : (tensor<256x3x32x32xf32>, tensor<3x3x3x16xf32>) -> tensor<256x16x32x32xf32> // OK
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 29 07:26:59 UTC 2024 - 59.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/decompose-hybrid-quantization.mlir
// CHECK: %[[VAL2:.+]] = "tfl.dequantize"(%[[VAL1]]) : (tensor<1x1x1x8x16x!quant.uniform<{{.+}}>>) -> tensor<1x1x1x8x16xf32> // CHECK: %[[VAL3:.+]] = "tfl.conv_3d"(%arg0, %[[VAL2]], %[[VAL0]]) <{dilation_d_factor = 1 : i32, dilation_h_factor = 1 : i32, dilation_w_factor = 1 : i32, fused_activation_function = "NONE", padding = "SAME", stride_d = 1 : i32, stride_h = 1 : i32, stride_w = 1 : i32}>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 13.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/tf-tfl-translate-serialize-stablehlo-conv.mlir
module { func.func @main(%arg0: tensor<4x68x68x3xf32>, %arg1: tensor<5x5x3x8xf32>) -> tensor<4x64x64x8xf32> { %0 = "tf.Conv2D"(%arg0, %arg1) {padding = "VALID", strides = [1, 1, 1, 1]} : (tensor<4x68x68x3xf32>, tensor<5x5x3x8xf32>) -> tensor<4x64x64x8xf32> func.return %0 : tensor<4x64x64x8xf32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Feb 27 23:35:37 UTC 2023 - 425 bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/end2end/fake_quant_per_channel_4bit.pbtxt
key: "narrow_range" value { b: true } } attr { key: "num_bits" value { i: 4 } } } node { name: "BoxPredictor_4/ClassPredictor/Conv2D" op: "Conv2D" input: "input" input: "BoxPredictor_4/ClassPredictor/weights_quant/FakeQuantWithMinMaxVarsPerChannel" attr { key: "T" value { type: DT_FLOAT } } attr {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 18.1K bytes - Viewed (0)