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Results 1 - 5 of 5 for 1x7x7x8xf32 (0.19 sec)
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tensorflow/compiler/mlir/lite/stablehlo/tests/composite-lowering.mlir
return %2 : tensor<1x1x1x4xf32> } func.func private @XlaCallModule_aten.avg_pool2d.default.impl_2(%arg0: tensor<1x1x1x8xf32>) -> tensor<1x1x1x4xf32> // CHECK-LABEL: avg_pool2d_3 // CHECK: %cst = arith.constant dense<[0, 2, 3, 1]> : tensor<4xi32> // CHECK: %0 = "tfl.transpose"(%arg0, %cst) : (tensor<1x1x1x8xf32>, tensor<4xi32>) -> tensor<1x1x8x1xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 18:45:51 UTC 2024 - 32.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/components/tf_to_stablehlo.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 08 20:05:12 UTC 2024 - 13.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/defer_activation_transpose.mlir
stablehlo.return %3 : tensor<f32> }) {window_dimensions = array<i64: 1, 1, 2, 2>, window_strides = array<i64: 1, 1, 2, 2>} : (tensor<1x4x16x16xf32>, tensor<f32>) -> tensor<1x4x8x8xf32> return %2 : tensor<1x4x8x8xf32> } // CHECK-SAME: %[[ARG:.+]]: tensor<1x16x16x4xf32> // CHECK-DAG: %[[INIT_VALUE_CONST:.+]] = stablehlo.constant dense<0xFF800000> // Check that the body is not modified.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 18 20:32:46 UTC 2024 - 14.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/dilated-conv.mlir
// CHECK-NEXT: [[RESULT:%.*]] = "tf.Squeeze"([[CONV]]) <{squeeze_dims = [-3]}> : (tensor<1x1x128x8xf32>) -> tensor<1x128x8xf32> // CHECK-NEXT: return [[RESULT]] : tensor<1x128x8xf32> } func.func @testDilatedConv1DExpandHWithBiasAdd(%arg0: tensor<1x128x3xf32>, %arg1: tensor<1x5x3x8xf32>, %arg2: tensor<8xf32>) -> tensor<1x128x8xf32> {
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/quantization/stablehlo/tests/pipelines/process_nchw_tensor.mlir
// CHECK: %[[CONV:.+]] = stablehlo.convolution(%[[TRANSPOSE_0]], %[[CONST]]) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {pad = {{\[\[}}1, 1], [1, 1]]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x4x4x8xf32>, tensor<3x3x8x8xf32>) -> tensor<1x4x4x8xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 18 20:32:46 UTC 2024 - 12.6K bytes - Viewed (0)