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Results 1 - 3 of 3 for conv3d (0.82 sec)
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tensorflow/compiler/mlir/tf2xla/tests/legalize-tf.mlir
// CHECK-SAME: [[ARG:%.+]]: tensor<2x12x21x7xf16> // CHECK: [[CONV32:%.+]] = mhlo.convert %arg0 : (tensor<2x12x21x7xf16>) -> tensor<2x12x21x7xf32> // CHECK: [[ZERO:%.+]] = mhlo.constant dense<0.000000e+00> : tensor<f32> // CHECK: [[DIVIDEND:%.+]] = "mhlo.reduce_window"([[CONV32]], [[ZERO]]) // CHECK-SAME: window_dimensions = dense<[1, 2, 2, 1]>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon May 06 18:46:23 UTC 2024 - 335.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/legalize_hlo.mlir
// CHECK: %[[CONV:.*]] = "tf.Conv2D"(%[[SLICED_ARG0]], %[[ARG1]]) // CHECK-SAME: explicit_paddings = [0, 0, 4, 0, 0, 2, 0, 0] // CHECK-SAME: (tensor<128x5x4x64xf32>, tensor<3x2x64x4xf32>) -> tensor<128x4x3x4xf32> // CHECK: return %[[CONV]] : tensor<128x4x3x4xf32> // CHECK: }
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/tf2xla/transforms/legalize_tf.cc
}; using ConvertConv2DDynamic = ConvertConvDynamic<TF::Conv2DOp, /*num_spatial_dims=*/2>; // Converts the TensorFlow conv op in template to the generic HLO conv op by // converting TensorFlow op attributes to HLO op attributes. // // Sample result for Conv2D: // // %conv = "mhlo.convolution"(%input, %filter) { // strides = [1, 2], // paddings = [[1, 0], [1, 1]], // ... // } //
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 20:00:43 UTC 2024 - 291.8K bytes - Viewed (0)