Searched refs:SHAPE (Results 1 – 25 of 83) sorted by relevance
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14 // CHECK: %[[SHAPE:[0-9]*]] = "tf.Shape"(%[[ARG_0]])16 // CHECK: %[[OP_A:[0-9]*]] = "tf.opA"(%[[SHAPE]], %[[RI]])17 // CHECK: tf_device.return %[[SHAPE]], %[[OP_A]]30 // CHECK: %[[SHAPE:[0-9]*]] = "tf.Shape"(%[[ARG_1]])32 // CHECK: tf_device.return %[[SHAPE]]64 // CHECK: %[[SHAPE:[0-9]*]] = "tf.Shape"(%[[ARG_2]])66 // CHECK: %[[OP_A:[0-9]*]] = "tf.opA"(%[[SHAPE]], %[[RJ]])67 // CHECK: tf_device.return %[[SHAPE]], %[[OP_A]]99 // CHECK: %[[SHAPE:[0-9]*]] = "tf.Shape"(%[[READ_VAR]])101 // CHECK: tf_device.return %[[SHAPE]][all …]
2 …-propagate-shape-knowledge-to-kernels -split-input-file | FileCheck %s --check-prefixes=CHECK,SHAPE31 …// SHAPE-SAME: %[[ARG0:.*]]: !llvm.ptr<f32>, %[[ARG1:.*]]: !llvm.ptr<f32>, %[[ARG2:.*]]: i64, %[[A…38 // SHAPE-NEXT: llvm.insertvalue %[[ARG0]]43 // SHAPE-NEXT: llvm.insertvalue %[[ARG2]]48 // SHAPE-NEXT: llvm.insertvalue %[[ARG4]]53 // SHAPE-NEXT: llvm.insertvalue %[[ARG5]]58 // SHAPE-NEXT: llvm.insertvalue %[[ARG7]]61 // SHAPE-NEXT: llvm.insertvalue %[[ARG3]]64 // SHAPE-NEXT: llvm.insertvalue %[[ARG4]]111 …// SHAPE: llvm.mlir.undef : !llvm.struct<(ptr<f32>, ptr<f32>, i64, array<1 x i64>, array<1 x i64>)>[all …]
4 …i1, %[[CALLABLE:.*]]: !tf_framework.jit_callable, %[[SIZE:.*]]: index, %[[SHAPE:.*]]: memref<?xind…15 // CHECK: %[[RESHAPE:.*]] = memref.reshape %[[ALLOC]](%[[SHAPE]])
12 // CHECK: %[[SHAPE:.*]] = shape.shape_of %arg013 // CHECK: %[[ELEMENT_COUNT:.*]] = shape.num_elements %[[SHAPE:.*]] : tensor<?xindex> -> index
15 // CHECK: %[[SHAPE:.*]] = tensor.from_elements24 // CHECK: %[[EL0:.*]] = tensor.extract %[[SHAPE]][%[[C0]]] : tensor<3xi64>26 // CHECK: %[[EL1:.*]] = tensor.extract %[[SHAPE]][%[[C1]]] : tensor<3xi64>33 // CHECK: %[[EL2:.*]] = tensor.extract %[[SHAPE]][%[[C2]]] : tensor<3xi64>59 // CHECK: %[[SHAPE:.*]] = tensor.from_elements69 // CHECK: %[[EL0:.*]] = tensor.extract %[[SHAPE]][%[[C0]]] : tensor<3xi64>71 // CHECK: %[[EL1:.*]] = tensor.extract %[[SHAPE]][%[[C1]]] : tensor<3xi64>78 // CHECK: %[[EL2:.*]] = tensor.extract %[[SHAPE]][%[[C2]]] : tensor<3xi64>103 // CHECK: %[[SHAPE:.*]] = tensor.from_elements105 // CHECK: %[[BSHAPE:.*]] = memref.buffer_cast %[[SHAPE]]
10 // CHECK-SAME: ([[ARG:%.*]]: memref<*xf32>, [[SHAPE:%.*]]: memref<1xi32>)11 // CHECK-NEXT: memref.reshape [[ARG]]([[SHAPE]])23 // CHECK-SAME: ([[ARG:%.*]]: memref<?xf32>, [[SHAPE:%.*]]: memref<?xi32>)24 // CHECK-NEXT: memref.reshape [[ARG]]([[SHAPE]])
5 // CHECK-SAME: (%[[ARG:.*]]: memref<?x?xf32>, %[[SHAPE:.*]]: memref<3xindex>) -> memref<?x?x?xf32>8 // CHECK: %[[DIM0:.*]] = memref.load %[[SHAPE]][%c0]9 // CHECK: %[[DIM1:.*]] = memref.load %[[SHAPE]][%c1]10 // CHECK: %[[DIM2:.*]] = memref.load %[[SHAPE]][%c2]12 // CHECK: "lmhlo.dynamic_reshape"(%[[ARG]], %[[SHAPE]], %[[OUTPUT]])22 // CHECK-SAME: (%[[ARG:.*]]: memref<?x?xf32>, %[[SHAPE:.*]]: memref<3xindex>) -> memref<?x?x?xf32>25 // CHECK: %[[DIM0:.*]] = memref.load %[[SHAPE]][%c0]26 // CHECK: %[[DIM1:.*]] = memref.load %[[SHAPE]][%c1]27 // CHECK: %[[DIM2:.*]] = memref.load %[[SHAPE]][%c2]29 // CHECK: "lmhlo.dynamic_broadcast_in_dim"(%[[ARG]], %[[SHAPE]], %[[OUTPUT]])[all …]
7 // CHECK: %[[SHAPE:.*]] = shape.shape_of %[[ARG]] : tensor<?x32xi16> -> tensor<?xindex>8 // CHECK: "use"(%[[SHAPE]])21 // CHECK: %[[SHAPE:.*]] = shape.shape_of %[[ARG0]] : tensor<?x32xf16> -> tensor<?xindex>22 // CHECK: "use"(%[[SHAPE]])122 // CHECK: %[[SHAPE:.*]] = shape.shape_of %[[DUMMY_TENSOR]]123 // CHECK: shape.assuming_yield %[[ARG1]], %[[DUMMY_TENSOR]], %[[SHAPE]]224 // CHECK: %[[SHAPE:.*]] = shape.shape_of %[[ARG1]]227 // CHECK: return %[[SHAPE]]241 // CHECK: %[[SHAPE:.*]] = shape.shape_of %[[ARG1]]246 // CHECK: return %[[SHAPE]]
158 // CHECK-SCF: %[[SHAPE:.*]] = shape.shape_of %[[ARG]]159 // CHECK-SCF: %[[N:.*]] = shape.num_elements %[[SHAPE]]165 // CHECK-SCF: %[[RES:.*]] = "mhlo.dynamic_reshape"(%[[UNSHAPED_RES]], %[[SHAPE]]) : (tensor<?…227 // CHECK-SCF: %[[SHAPE:.*]] = shape.shape_of %[[ARG]]228 // CHECK-SCF: %[[N:.*]] = shape.num_elements %[[SHAPE]]234 // CHECK-SCF: %[[RES:.*]] = "mhlo.dynamic_reshape"(%[[UNSHAPED_RES]], %[[SHAPE]]) : (tensor<?x…294 // CHECK-SCF: %[[SHAPE:.*]] = shape.shape_of %[[ARG]]295 // CHECK-SCF: %[[N:.*]] = shape.num_elements %[[SHAPE]]299 // CHECK-SCF: %[[RES:.*]] = "mhlo.dynamic_reshape"(%[[UNSHAPED_RES]], %[[SHAPE]]) : (tensor<?…323 // CHECK-SCF: %[[SHAPE:.*]] = shape.shape_of %[[ARG]][all …]
4 // CHECK-SAME: %[[ARG:.*]]: tensor<?x?xf32>, %[[SHAPE:.*]]: tensor<3xindex>9 // CHECK-DAG: %[[SHAPE_D0:.*]] = tensor.extract %[[SHAPE]][%[[C0]]]10 // CHECK-DAG: %[[SHAPE_D1:.*]] = tensor.extract %[[SHAPE]][%[[C1]]]11 // CHECK-DAG: %[[SHAPE_D2:.*]] = tensor.extract %[[SHAPE]][%[[C2]]]25 // CHECK-SAME: %[[ARG:.*]]: tensor<?x?xf32>, %[[SHAPE:.*]]: tensor<3xindex>28 // CHECK: %[[BCAST:.*]] = "mhlo.dynamic_broadcast_in_dim"(%[[ARG]], %[[SHAPE]])39 // CHECK-SAME: %[[ARG:.*]]: tensor<?x?x?xf32>, %[[SHAPE:.*]]: tensor<4xindex>45 // CHECK-DAG: %[[SHAPE_D0:.*]] = tensor.extract %[[SHAPE]][%[[C0]]]46 // CHECK-DAG: %[[SHAPE_D1:.*]] = tensor.extract %[[SHAPE]][%[[C1]]]47 // CHECK-DAG: %[[SHAPE_D2:.*]] = tensor.extract %[[SHAPE]][%[[C2]]][all …]
5 // CHECK-SAME: %[[ARG0:.*]]: tensor<16x?xf32>, %[[ARG1:.*]]: tensor<16x?xf32>, %[[SHAPE:.*]]: tens…8 // CHECK-DAG: %[[BCASTED_ARG0:.*]] = "mhlo.dynamic_broadcast_in_dim"(%[[ARG0]], %[[SHAPE]])9 // CHECK-DAG: %[[BCASTED_ARG1:.*]] = "mhlo.dynamic_broadcast_in_dim"(%[[ARG1]], %[[SHAPE]])28 // CHECK-SAME: %[[ARG0:.*]]: tensor<16x?xf32>, %[[ARG1:.*]]: tensor<16x?xf32>, %[[SHAPE:.*]]: tens…31 // CHECK-DAG: %[[BCASTED_ARG0:.*]] = "mhlo.dynamic_broadcast_in_dim"(%[[ARG0]], %[[SHAPE]])32 // CHECK-DAG: %[[BCASTED_ARG1:.*]] = "mhlo.dynamic_broadcast_in_dim"(%[[ARG1]], %[[SHAPE]])87 // CHECK-DAG: %[[SHAPE:.*]] = shape.shape_of %[[ARG2]]88 …// CHECK-DAG: %[[BCASTED_ARG0:.*]] = "mhlo.dynamic_broadcast_in_dim"(%[[ARG0]], %[[SHAPE]]) {broad…89 …// CHECK-DAG: %[[BCASTED_ARG1:.*]] = "mhlo.dynamic_broadcast_in_dim"(%[[ARG1]], %[[SHAPE]]) {broad…128 …<?x32xf32>, %[[ARG2:.*]]: tensor<?x32xf32>, %[[W:.*]]: !shape.witness, %[[SHAPE:.*]]: tensor<3xind…[all …]
8 // CHECK: %[[SHAPE:.*]] = shape.shape_of %[[ARG]]9 // CHECK: "use"(%[[SHAPE]])21 // CHECK: %[[SHAPE:.*]] = shape.shape_of %[[ARG0]]22 // CHECK: "use"(%[[SHAPE]])36 // CHECK: %[[SHAPE:.*]] = shape.shape_of %[[ARG0]] : tensor<?x32xf16> -> tensor<2xindex>37 // CHECK: %[[CASTED:.*]] = tensor.cast %[[SHAPE]] : tensor<2xindex> to tensor<?xindex>53 // CHECK: %[[SHAPE:.*]] = shape.shape_of %[[DUMMY_TENSOR]]54 // CHECK: shape.assuming_yield %[[ARG1]], %[[DUMMY_TENSOR]], %[[SHAPE]]
36 // CHECK-SAME: %[[ARG:.*]]: tensor<?x?xi32>, %[[SHAPE:.*]]: tensor<3xi64>53 // CHECK: %[[EL0:.*]] = tensor.extract %[[SHAPE]][%[[C0]]] : tensor<3xi64>55 // CHECK: %[[EL1:.*]] = tensor.extract %[[SHAPE]][%[[C1]]] : tensor<3xi64>61 // CHECK: %[[EL2:.*]] = tensor.extract %[[SHAPE]][%[[C2]]] : tensor<3xi64>76 // CHECK-SAME: %[[ARG:.*]]: tensor<?x?xi32>, %[[SHAPE:.*]]: tensor<3xi64>83 // CHECK-DAG: %[[BSHAPE:.*]] = bufferization.to_memref %[[SHAPE]]
9 // CHECK: %[[SHAPE:.*]] = shape.shape_of %[[ARG]] : tensor<?x32xi16> -> tensor<?xindex>10 // CHECK: "use"(%[[SHAPE]])23 // CHECK: %[[SHAPE:.*]] = shape.shape_of %[[ARG0]] : tensor<?x32xf16> -> tensor<?xindex>24 // CHECK: "use"(%[[SHAPE]])55 // CHECK: %[[SHAPE:.*]] = shape.shape_of %[[DUMMY_TENSOR]]56 // CHECK: shape.assuming_yield %[[ARG1]], %[[DUMMY_TENSOR]], %[[SHAPE]]158 // CHECK: %[[SHAPE:.*]] = shape.shape_of %[[ARG1]]161 // CHECK: return %[[SHAPE]]175 // CHECK: %[[SHAPE:.*]] = shape.shape_of %[[ARG1]]180 // CHECK: return %[[SHAPE]]
1 …INT32,DT_RESOURCE(DT_INT32)" -tf-output-arrays=p,x -o - | FileCheck %s -check-prefix=CHECK-NO-SHAPE3 …DT_RESOURCE(512,1024:DT_INT32)" -tf-output-arrays=p,x -o - | FileCheck %s -check-prefix=CHECK-SHAPE49 # CHECK-NO-SHAPE: func @main(%arg0: tensor<i32>, %arg1: tensor<!tf_type.resource<tensor<i32>>>) -> …51 # CHECK-SHAPE: func @main(%arg0: tensor<512x1024xi32>, %arg1: tensor<!tf_type.resource<tensor<512x1…
48 // TIER1: %[[SHAPE:.*]] = "tf.Shape"(%[[CLUSTER]])49 // TIER1: return %[[SHAPE]]51 // REDUCTIONS: %[[SHAPE:.*]] = "tf.Shape"(%[[CLUSTER]])52 // REDUCTIONS: return %[[SHAPE]]
22 // CHECK: %[[SHAPE:.*]] = "tf.Shape"(%[[CLUSTER]])23 // CHECK: return %[[SHAPE]]
73 // TILE-CHECK-SAME: %[[ARG:.*]]: tensor<?xf32>, %[[SHAPE:.*]]: tensor<2xindex>82 // POINT-CHECK-SAME: %[[ARG:.*]]: tensor<?xf32>, %[[SHAPE:.*]]: tensor<2xindex>101 // TILE-CHECK-SAME: %[[ARG:.*]]: tensor<?x?xf32>, %[[SHAPE:.*]]: tensor<2xindex>114 // POINT-CHECK-SAME: %[[ARG:.*]]: tensor<?x?xf32>, %[[SHAPE:.*]]: tensor<2xindex>
158 // CHECK-SCF: %[[SHAPE:.*]] = shape.shape_of %[[ARG]]159 // CHECK-SCF: %[[N:.*]] = shape.num_elements %[[SHAPE]]165 // CHECK-SCF: %[[RES:.*]] = mhlo.dynamic_reshape %[[UNSHAPED_RES]], %[[SHAPE]] : (tensor<?xf3…227 // CHECK-SCF: %[[SHAPE:.*]] = shape.shape_of %[[ARG]]228 // CHECK-SCF: %[[N:.*]] = shape.num_elements %[[SHAPE]]234 // CHECK-SCF: %[[RES:.*]] = mhlo.dynamic_reshape %[[UNSHAPED_RES]], %[[SHAPE]] : (tensor<?xf32…294 // CHECK-SCF: %[[SHAPE:.*]] = shape.shape_of %[[ARG]]295 // CHECK-SCF: %[[N:.*]] = shape.num_elements %[[SHAPE]]299 // CHECK-SCF: %[[RES:.*]] = mhlo.dynamic_reshape %[[UNSHAPED_RES]], %[[SHAPE]] : (tensor<?xf3…323 // CHECK-SCF: %[[SHAPE:.*]] = shape.shape_of %[[ARG]][all …]
65 // CHECK-NEXT: [[SHAPE:%.*]] = "tf.Shape"(%arg0) : (tensor<?x3xf32>) -> tensor<?xi32>66 // CHECK-NEXT: [[RESHAPE:%.*]] = "tf.Reshape"(%arg0, [[SHAPE]]) : (tensor<?x3xf32>, tensor<?xi32>)…175 // CHECK-DAG: [[SHAPE:%.*]] = "tf.Concat"([[ZERO2]], [[DIM0]], %arg0) : (tensor<i32>, tensor<1xi32…177 // CHECK: [[LIST:%.*]] = "tf.Fill"([[SHAPE]], [[VALUES]]) : (tensor<4xi32>, tensor<f32>) -> te…208 // CHECK-DAG: [[SHAPE:%.*]] = "tf.Concat"([[ZERO2]], [[DIM0]], [[ELEMENT_SHAPE]]) : (tensor<i32>, …210 // CHECK: [[LIST:%.*]] = "tf.Fill"([[SHAPE]], [[VALUES]]) : (tensor<3xi32>, tensor<f32>) -> te…225 // CHECK-DAG: [[SHAPE:%[0-9]+]] = "tf.Shape"(%arg3) : (tensor<2xf32>) -> tensor<?xi32>229 // CHECK-DAG: [[FINAL_SHAPE:%[0-9]+]] = "tf.Concat"([[CST0]], [[EXPAND_DIM]], [[SHAPE]]) : (tensor…263 // CHECK-DAG: [[SHAPE:%.*]] = "tf.Concat"([[ZERO]], [[DIM0]], [[ELEM_SHAPE]]) : (tensor<i32>, tens…265 // CHECK: [[LIST:%.*]] = "tf.Fill"([[SHAPE]], [[VALUES]]) : (tensor<4xi32>, tensor<f32>) -> te…[all …]
402 debug_event_pb2.TensorDebugMode.SHAPE):410 tensor_debug_mode == debug_event_pb2.TensorDebugMode.SHAPE and490 debug_event_pb2.TensorDebugMode.SHAPE,517 elif tensor_debug_mode == debug_event_pb2.TensorDebugMode.SHAPE:815 debug_event_pb2.TensorDebugMode.SHAPE,
39 SHAPE, // "shape" (tf.TensorShape) enumerator
20 "operator_codes": [ { "builtin_code": "SHAPE" } ], in ShapeFixture()