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Results 1 - 10 of 34 for 3x5x4xf32 (0.13 sec)
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tensorflow/compiler/mlir/tensorflow/tests/einsum.mlir
%0 = "tf.Einsum"(%arg0, %arg1) {T = "tfdtype$DT_FLOAT", equation = "ijk,ikm->ijm"}: (tensor<3x4x5xf32>, tensor<3x5x6xf32>) -> tensor<3x4x6xf32> func.return %0 : tensor<3x4x6xf32> // CHECK-LABEL: einsum_basic // CHECK: "tf.BatchMatMulV2"(%arg0, %arg1) <{adj_x = false, adj_y = false}> : (tensor<3x4x5xf32>, tensor<3x5x6xf32>) -> tensor<3x4x6xf32> }
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: %[[LHS_SPLIT:.*]]:6 = "tf.Split"(%[[SPLITTING_AXIS]], %[[LHS_RESHAPED]]) : (tensor<i32>, tensor<6x5x4xf32>) -> (tensor<1x5x4xf32>, tensor<1x5x4xf32>, tensor<1x5x4xf32>, tensor<1x5x4xf32>, tensor<1x5x4xf32>, tensor<1x5x4xf32>) // CHECK: %[[LHS_1:.*]] = "tf.Reshape"(%[[LHS_SPLIT]]#0, %[[MATMUL_LHS_SHAPE]]) : (tensor<1x5x4xf32>, tensor<2xi64>) -> tensor<5x4xf32>
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/tensorflow/tests/lower_tf.mlir
// CHECK: %[[SLICE3:.*]] = "tf.Slice"(%[[CONCAT]], %[[CST5]], %[[CST6]]) : (tensor<3x8x4xi32>, tensor<3xi64>, tensor<3xi64>) -> tensor<3x6x4xi32> // CHECK: %[[CONCAT1:.*]] = "tf.ConcatV2"(%[[SLICE2]], %[[SLICE3]], %[[CST7]]) : (tensor<3x2x4xi32>, tensor<3x6x4xi32>, tensor<i32>) -> tensor<3x8x4xi32> // CHECK: return %[[CONCAT1]] : tensor<3x8x4xi32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 05 18:35:42 UTC 2024 - 92K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/tfl_legalize_hlo.mlir
// CHECK-NEXT: %[[RESHAPED_BMM:.*]] = mhlo.reshape %[[BMM_0]] // CHECK-NEXT: return %[[RESHAPED_BMM]] : tensor<3x5x1x4xf32> } func.func @convert_dot_general_repeated(%arg0: tensor<1x1x1024xf32>, %arg1: tensor<1024x1024xf32>) -> tensor<1x1x1024xf32> {
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/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/tensorflow/tests/batchmatmul_to_einsum.mlir
// CHECK-LABEL: test_batch_matmul_to_einsum // CHECK: "tf.Einsum"(%arg0, %arg1) <{equation = "...mk,...kn->...mn"}> : (tensor<1x2x3xf32>, tensor<3x4xf32>) -> tensor<1x2x4xf32> %0 = "tf.BatchMatMul"(%arg0, %arg1) {adj_x = false, adj_y = false} : (tensor<1x2x3xf32>, tensor<3x4xf32>) -> tensor<1x2x4xf32> func.return %0: tensor<1x2x4xf32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/tests/legalize-tf-include-tf2xla-fallback.mlir
%0 = "tf.BatchMatMulV2"(%arg0, %arg1) {T = f32, adj_x = false, adj_y = false, grad_x = false, grad_y = false, device = ""} : (tensor<1x4x2xf32>, tensor<3x2x4xf32>) -> tensor<3x4x4xf32> func.return %0 : tensor<3x4x4xf32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Nov 16 19:04:03 UTC 2023 - 3.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/ops/stablehlo_op_quant_spec_test.cc
return %0 : tensor<1x1x4xf32> } )mlir"; OwningOpRef<ModuleOp> module_op = ParseModuleOpString(kModuleXlaCallModuleOpWithDefaultQuantizationMethod); ASSERT_TRUE(module_op);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 04 07:19:09 UTC 2024 - 14.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/api/v2/legalize_tf_test.cc
func.func @main() -> (tensor<1x4x4xf32>) { %%arg0 = "tf.Const"() {value = dense<-3.0> : tensor<1x4x2xf32>} : () -> tensor<1x4x2xf32> %%arg1 = "tf.Const"() {value = dense<-3.0> : tensor<1x2x4xf32>} : () -> tensor<1x2x4xf32> %%1 = "tf.%s"(%%arg0, %%arg1) {T = f32, adj_x = false, adj_y = false, grad_x = false, grad_y = false, device = ""} : (tensor<1x4x2xf32>, tensor<1x2x4xf32>) -> tensor<1x4x4xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 13 23:59:33 UTC 2024 - 16.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/fold-broadcast.mlir
func.func @broadcast_mul_implicit_no_fold(%arg0: tensor<5x7xf32>, %arg1: tensor<5xf32>) -> tensor<3x5x7xf32> { %cst = arith.constant dense<[3, 5, 7]> : tensor<3xi32> %0 = "tf.BroadcastTo"(%arg1, %cst) : (tensor<5xf32>, tensor<3xi32>) -> tensor<3x5x7xf32> %1 = "tf.Mul"(%arg0, %0) : (tensor<5x7xf32>, tensor<3x5x7xf32>) -> tensor<3x5x7xf32> func.return %1 : tensor<3x5x7xf32> // CHECK: %[[C0:.*]] = arith.constant dense<[3, 5, 7]> : tensor<3xi32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 6.6K bytes - Viewed (0)