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Results 1 - 10 of 17 for 3x2x4x6xf32 (0.2 sec)
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tensorflow/compiler/mlir/lite/stablehlo/tests/tfl_legalize_hlo.mlir
// CHECK-NEXT: return %2 : tensor<4x?xf32> } // - dot_general // func.func @convert_dot_general(%arg0: tensor<3x2x6x5x1xf32>, %arg1: tensor<3x2x4x6xf32>) -> tensor<3x5x1x4xf32> { %0 = "mhlo.dot_general"(%arg0, %arg1) { dot_dimension_numbers = #mhlo.dot< lhs_batching_dimensions = [0], lhs_contracting_dimensions = [1, 2],
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 40.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/einsum.mlir
// CHECK: return %[[v3]] : tensor<2x7x11x5xf32> } func.func @einsum_4d_1(%arg0: tensor<3x4x5x6xf32>, %arg1: tensor<3x7x5x6xf32>) -> tensor<3x5x4x7xf32> { %0 = "tf.Einsum"(%arg0, %arg1) {T = "tfdtype$DT_FLOAT", equation = "jbki,jfki->jkbf"}: (tensor<3x4x5x6xf32>, tensor<3x7x5x6xf32>) -> tensor<3x5x4x7xf32> func.return %0 : tensor<3x5x4x7xf32> // CHECK-LABEL: einsum_4d_1
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 05 18:35:42 UTC 2024 - 25.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/unroll-batch-matmul.mlir
// CHECK: return %[[RESULT]] : tensor<2x3x4x6xf32> } // ----- func.func @batchMatMulTwoDimAdjXY(%arg0: tensor<2x3x5x4xf32>, %arg1: tensor<2x3x6x5xf32>) -> tensor<2x3x4x6xf32> { %0 = "tf.BatchMatMul"(%arg0, %arg1) {adj_x = true, adj_y = true} : (tensor<2x3x5x4xf32>, tensor<2x3x6x5xf32>) -> tensor<2x3x4x6xf32> func.return %0 : tensor<2x3x4x6xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Dec 06 18:42:28 UTC 2023 - 63.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/legalize_hlo.mlir
// CHECK: %[[VAL_4:.*]] = "tf.Const"() <{value = dense<[0, 1, 3, 2]> : tensor<4xi64>}> : () -> tensor<4xi64> // CHECK: %[[VAL_5:.*]] = "tf.Transpose"(%[[VAL_1]], %[[VAL_4]]) : (tensor<3x2x4x6xf32>, tensor<4xi64>) -> tensor<3x2x6x4xf32> // CHECK: %[[VAL_6:.*]] = arith.constant dense<[3, 5, 12]> : tensor<3xi64>
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/tensorflow/tests/cast_bf16_ops_to_f32.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 8.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/convert_tf_xla_op_to_tf_op.mlir
func.func @xla_dot_v2(%arg0: tensor<?x2x3xf32>, %arg1: tensor<3x4x5xf32>) -> (tensor<?x2x4x5xf32>) { %0 = "tf.XlaDotV2"(%arg0, %arg1) {device = "", dimension_numbers = "\0A\01\02\12\01\00", precision_config = ""} : (tensor<?x2x3xf32>, tensor<3x4x5xf32>) -> tensor<?x2x4x5xf32> func.return %0 : tensor<?x2x4x5xf32> } // CHECK: func @xla_dot_v2
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 3.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/tests/legalize-tf-BatchMatMulV2.mlir
func.func @batchmatmulv2_basic(%arg0: tensor<1x4x2xf32>, %arg1: tensor<3x2x4xf32>) -> tensor<3x4x4xf32> { // CHECK-LABEL: func @batchmatmulv2_basic // CHECK-SAME: ([[LHS:%.*]]: tensor<1x4x2xf32>, [[RHS:%.*]]: tensor<3x2x4xf32>) -> tensor<3x4x4xf32> // CHECK: [[LHSSHAPE:%.*]] = shape.shape_of [[LHS]] : tensor<1x4x2xf32> // CHECK: [[RHSSHAPE:%.*]] = shape.shape_of [[RHS]] : tensor<3x2x4xf32> // CHECK: [[CM2:%.*]] = arith.constant -2 : index
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 15:32:52 UTC 2024 - 5.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/lift_quantizable_spots_as_functions.mlir
func.func @conv_fn(%arg0: tensor<1x3x3x4xf32>) -> tensor<1x3x3x4xf32> { %0 = stablehlo.constant dense<2.000000e+00> : tensor<3x3x4x4xf32> %1 = stablehlo.convolution(%arg0, %0) 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<1x3x3x4xf32>, tensor<3x3x4x4xf32>) -> tensor<1x3x3x4xf32> func.return %1: tensor<1x3x3x4xf32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 10 04:07:09 UTC 2024 - 49.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/lift_as_function_call_test.cc
%0 = stablehlo.constant dense<2.000000e+00> : tensor<3x3x4x4xf32> %1 = stablehlo.convolution(%arg0, %0) 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<1x3x3x4xf32>, tensor<3x3x4x4xf32>) -> tensor<1x3x3x4xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 10 04:07:09 UTC 2024 - 26.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/tests/legalize-tf-include-tf2xla-fallback.mlir
// fallback lowering is preferred for static shaped operands when available. // CHECK-LABEL: batchmatmulv2 func.func @batchmatmulv2(%arg0: tensor<1x4x2xf32>, %arg1: tensor<3x2x4xf32>) -> tensor<3x4x4xf32> { // NO_FALLBACK: mhlo.dynamic_broadcast_in_dim // NO_FALLBACK: mhlo.dot_general // SUPPORTED_FALLBACK_DEVICE: mhlo.reduce // SUPPORTED_FALLBACK_DEVICE: mhlo.dot_general
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Nov 16 19:04:03 UTC 2023 - 3.2K bytes - Viewed (0)