mirror of https://github.com/llvm/torch-mlir
575 lines
40 KiB
MLIR
575 lines
40 KiB
MLIR
// RUN: torch-mlir-opt <%s -convert-torch-to-mhlo -split-input-file -verify-diagnostics | FileCheck %s
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// CHECK-LABEL: func.func @torch.aten.slice.strided$slice_like(
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// CHECK-SAME: %[[ARG0:.*]]: !torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[?,?,?],f32> {
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// CHECK: %[[T0:.*]] = torch_c.to_builtin_tensor %[[ARG0]] : !torch.vtensor<[?,?,?],f32> -> tensor<?x?x?xf32>
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// CHECK: %[[INT0:.*]] = torch.constant.int 0
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// CHECK: %[[T1:.*]] = torch_c.to_i64 %[[INT0]]
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// CHECK: %[[INT2:.*]] = torch.constant.int 2
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// CHECK: %[[T2:.*]] = torch_c.to_i64 %[[INT2]]
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// CHECK: %[[INT9223372036854775807:.*]] = torch.constant.int 9223372036854775807
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// CHECK: %[[T3:.*]] = torch_c.to_i64 %[[INT9223372036854775807]]
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// CHECK: %[[C0:.*]] = arith.constant 0 : index
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// CHECK: %[[DIM:.*]] = tensor.dim %[[T0]], %[[C0]] : tensor<?x?x?xf32>
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// CHECK: %[[T4:.*]] = arith.index_cast %[[DIM]] : index to i64
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// CHECK: %[[C0_I64:.*]] = arith.constant 0 : i64
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// CHECK: %[[T5:.*]] = arith.subi %[[C0_I64]], %[[T4]] : i64
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// CHECK: %[[T6:.*]] = arith.maxsi %[[T5]], %[[T1]] : i64
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// CHECK: %[[T7:.*]] = arith.minsi %[[T4]], %[[T6]] : i64
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// CHECK: %[[T8:.*]] = arith.addi %[[T4]], %[[T7]] : i64
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// CHECK: %[[T9:.*]] = arith.cmpi sge, %[[T7]], %[[C0_I64]] : i64
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// CHECK: %[[T10:.*]] = arith.select %[[T9]], %[[T7]], %[[T8]] : i64
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// CHECK: %[[C0_I64_0:.*]] = arith.constant 0 : i64
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// CHECK: %[[T11:.*]] = arith.subi %[[C0_I64_0]], %[[T4]] : i64
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// CHECK: %[[T12:.*]] = arith.maxsi %[[T11]], %[[T3]] : i64
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// CHECK: %[[T13:.*]] = arith.minsi %[[T4]], %[[T12]] : i64
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// CHECK: %[[T14:.*]] = arith.addi %[[T4]], %[[T13]] : i64
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// CHECK: %[[T15:.*]] = arith.cmpi sge, %[[T13]], %[[C0_I64_0]] : i64
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// CHECK: %[[T16:.*]] = arith.select %[[T15]], %[[T13]], %[[T14]] : i64
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// CHECK: %[[C0_1:.*]] = arith.constant 0 : index
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// CHECK: %[[DIM_2:.*]] = tensor.dim %[[T0]], %[[C0_1]] : tensor<?x?x?xf32>
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// CHECK: %[[T17:.*]] = arith.index_cast %[[DIM_2]] : index to i64
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// CHECK: %[[C1:.*]] = arith.constant 1 : index
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// CHECK: %[[DIM_3:.*]] = tensor.dim %[[T0]], %[[C1]] : tensor<?x?x?xf32>
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// CHECK: %[[T18:.*]] = arith.index_cast %[[DIM_3]] : index to i64
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// CHECK: %[[C2:.*]] = arith.constant 2 : index
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// CHECK: %[[DIM_4:.*]] = tensor.dim %[[T0]], %[[C2]] : tensor<?x?x?xf32>
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// CHECK: %[[T19:.*]] = arith.index_cast %[[DIM_4]] : index to i64
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// CHECK: %[[C0_I64_5:.*]] = arith.constant 0 : i64
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// CHECK: %[[C1_I64:.*]] = arith.constant 1 : i64
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// CHECK: %[[T20:.*]] = arith.cmpi eq, %[[T16]], %[[C0_I64_5]] : i64
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// CHECK: %[[T21:.*]] = arith.select %[[T20]], %[[T17]], %[[T16]] : i64
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// CHECK: %[[FROM_ELEMENTS:.*]] = tensor.from_elements %[[T10]], %[[C0_I64_5]], %[[C0_I64_5]] : tensor<3xi64>
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// CHECK: %[[FROM_ELEMENTS_6:.*]] = tensor.from_elements %[[T21]], %[[T18]], %[[T19]] : tensor<3xi64>
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// CHECK: %[[FROM_ELEMENTS_7:.*]] = tensor.from_elements %[[T2]], %[[C1_I64]], %[[C1_I64]] : tensor<3xi64>
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// CHECK: %[[T22:.*]] = mhlo.real_dynamic_slice %[[T0]], %[[FROM_ELEMENTS]], %[[FROM_ELEMENTS]]_6, %[[FROM_ELEMENTS]]_7 : (tensor<?x?x?xf32>, tensor<3xi64>, tensor<3xi64>, tensor<3xi64>) -> tensor<?x?x?xf32>
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// CHECK: %[[T23:.*]] = torch_c.from_builtin_tensor %[[T22]] : tensor<?x?x?xf32> -> !torch.vtensor<[?,?,?],f32>
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// CHECK: return %[[T23]] : !torch.vtensor<[?,?,?],f32>
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func.func @torch.aten.slice.strided$slice_like(%arg0: !torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[?,?,?],f32> {
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%int0 = torch.constant.int 0
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%int2 = torch.constant.int 2
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%int9223372036854775807 = torch.constant.int 9223372036854775807
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%0 = torch.aten.slice.Tensor %arg0, %int0, %int0, %int9223372036854775807, %int2 : !torch.vtensor<[?,?,?],f32>, !torch.int, !torch.int, !torch.int, !torch.int -> !torch.vtensor<[?,?,?],f32>
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return %0 : !torch.vtensor<[?,?,?],f32>
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}
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// -----
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// CHECK-LABEL: func.func @torch.aten.slice.strided.static$slice_like(
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// CHECK-SAME: %[[ARG0:.*]]: !torch.vtensor<[4,65,256],f32>) -> !torch.vtensor<[2,65,256],f32> {
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// CHECK: %[[T0:.*]] = torch_c.to_builtin_tensor %[[ARG0]] : !torch.vtensor<[4,65,256],f32> -> tensor<4x65x256xf32>
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// CHECK: %[[INT0:.*]] = torch.constant.int 0
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// CHECK: %[[T1:.*]] = torch_c.to_i64 %[[INT0]]
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// CHECK: %[[INT2:.*]] = torch.constant.int 2
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// CHECK: %[[T2:.*]] = torch_c.to_i64 %[[INT2]]
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// CHECK: %[[INT9223372036854775807:.*]] = torch.constant.int 9223372036854775807
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// CHECK: %[[T3:.*]] = torch_c.to_i64 %[[INT9223372036854775807]]
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// CHECK: %[[C0:.*]] = arith.constant 0 : index
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// CHECK: %[[DIM:.*]] = tensor.dim %[[T0]], %[[C0]] : tensor<4x65x256xf32>
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// CHECK: %[[T4:.*]] = arith.index_cast %[[DIM]] : index to i64
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// CHECK: %[[C0_I64:.*]] = arith.constant 0 : i64
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// CHECK: %[[T5:.*]] = arith.subi %[[C0_I64]], %[[T4]] : i64
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// CHECK: %[[T6:.*]] = arith.maxsi %[[T5]], %[[T1]] : i64
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// CHECK: %[[T7:.*]] = arith.minsi %[[T4]], %[[T6]] : i64
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// CHECK: %[[T8:.*]] = arith.addi %[[T4]], %[[T7]] : i64
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// CHECK: %[[T9:.*]] = arith.cmpi sge, %[[T7]], %[[C0_I64]] : i64
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// CHECK: %[[T10:.*]] = arith.select %[[T9]], %[[T7]], %[[T8]] : i64
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// CHECK: %[[C0_I64_0:.*]] = arith.constant 0 : i64
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// CHECK: %[[T11:.*]] = arith.subi %[[C0_I64_0]], %[[T4]] : i64
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// CHECK: %[[T12:.*]] = arith.maxsi %[[T11]], %[[T3]] : i64
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// CHECK: %[[T13:.*]] = arith.minsi %[[T4]], %[[T12]] : i64
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// CHECK: %[[T14:.*]] = arith.addi %[[T4]], %[[T13]] : i64
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// CHECK: %[[T15:.*]] = arith.cmpi sge, %[[T13]], %[[C0_I64_0]] : i64
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// CHECK: %[[T16:.*]] = arith.select %[[T15]], %[[T13]], %[[T14]] : i64
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// CHECK: %[[C0_1:.*]] = arith.constant 0 : index
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// CHECK: %[[DIM_2:.*]] = tensor.dim %[[T0]], %[[C0_1]] : tensor<4x65x256xf32>
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// CHECK: %[[T17:.*]] = arith.index_cast %[[DIM_2]] : index to i64
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// CHECK: %[[C1:.*]] = arith.constant 1 : index
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// CHECK: %[[DIM_3:.*]] = tensor.dim %[[T0]], %[[C1]] : tensor<4x65x256xf32>
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// CHECK: %[[T18:.*]] = arith.index_cast %[[DIM_3]] : index to i64
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// CHECK: %[[C2:.*]] = arith.constant 2 : index
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// CHECK: %[[DIM_4:.*]] = tensor.dim %[[T0]], %[[C2]] : tensor<4x65x256xf32>
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// CHECK: %[[T19:.*]] = arith.index_cast %[[DIM_4]] : index to i64
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// CHECK: %[[C0_I64_5:.*]] = arith.constant 0 : i64
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// CHECK: %[[C1_I64:.*]] = arith.constant 1 : i64
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// CHECK: %[[T20:.*]] = arith.cmpi eq, %[[T16]], %[[C0_I64_5]] : i64
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// CHECK: %[[T21:.*]] = arith.select %[[T20]], %[[T17]], %[[T16]] : i64
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// CHECK: %[[FROM_ELEMENTS:.*]] = tensor.from_elements %[[T10]], %[[C0_I64_5]], %[[C0_I64_5]] : tensor<3xi64>
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// CHECK: %[[FROM_ELEMENTS_6:.*]] = tensor.from_elements %[[T21]], %[[T18]], %[[T19]] : tensor<3xi64>
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// CHECK: %[[FROM_ELEMENTS_7:.*]] = tensor.from_elements %[[T2]], %[[C1_I64]], %[[C1_I64]] : tensor<3xi64>
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// CHECK: %[[T22:.*]] = mhlo.real_dynamic_slice %[[T0]], %[[FROM_ELEMENTS]], %[[FROM_ELEMENTS]]_6, %[[FROM_ELEMENTS]]_7 : (tensor<4x65x256xf32>, tensor<3xi64>, tensor<3xi64>, tensor<3xi64>) -> tensor<2x65x256xf32>
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// CHECK: %[[T23:.*]] = torch_c.from_builtin_tensor %[[T22]] : tensor<2x65x256xf32> -> !torch.vtensor<[2,65,256],f32>
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// CHECK: return %[[T23]] : !torch.vtensor<[2,65,256],f32>
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func.func @torch.aten.slice.strided.static$slice_like(%arg0: !torch.vtensor<[4,65,256],f32>) -> !torch.vtensor<[2,65,256],f32> {
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%int0 = torch.constant.int 0
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%int2 = torch.constant.int 2
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%int9223372036854775807 = torch.constant.int 9223372036854775807
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%0 = torch.aten.slice.Tensor %arg0, %int0, %int0, %int9223372036854775807, %int2 : !torch.vtensor<[4,65,256],f32>, !torch.int, !torch.int, !torch.int, !torch.int -> !torch.vtensor<[2,65,256],f32>
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return %0 : !torch.vtensor<[2,65,256],f32>
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}
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// -----
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// CHECK-LABEL: func.func @torch.aten.slice.last$slice_like(
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// CHECK-SAME: %[[ARG0:.*]]: !torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[?,1,?],f32> {
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// CHECK: %[[T0:.*]] = torch_c.to_builtin_tensor %[[ARG0]] : !torch.vtensor<[?,?,?],f32> -> tensor<?x?x?xf32>
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// CHECK: %[[INT0:.*]] = torch.constant.int 0
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// CHECK: %[[T1:.*]] = torch_c.to_i64 %[[INT0]]
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// CHECK: %[[INT1:.*]] = torch.constant.int 1
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// CHECK: %[[T2:.*]] = torch_c.to_i64 %[[INT1]]
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// CHECK: %[[INT:.*]]-1 = torch.constant.int -1
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// CHECK: %[[T3:.*]] = torch_c.to_i64 %[[INT]]-1
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// CHECK: %[[C1:.*]] = arith.constant 1 : index
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// CHECK: %[[DIM:.*]] = tensor.dim %[[T0]], %[[C1]] : tensor<?x?x?xf32>
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// CHECK: %[[T4:.*]] = arith.index_cast %[[DIM]] : index to i64
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// CHECK: %[[C0_I64:.*]] = arith.constant 0 : i64
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// CHECK: %[[T5:.*]] = arith.subi %[[C0_I64]], %[[T4]] : i64
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// CHECK: %[[T6:.*]] = arith.maxsi %[[T5]], %[[T3]] : i64
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// CHECK: %[[T7:.*]] = arith.minsi %[[T4]], %[[T6]] : i64
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// CHECK: %[[T8:.*]] = arith.addi %[[T4]], %[[T7]] : i64
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// CHECK: %[[T9:.*]] = arith.cmpi sge, %[[T7]], %[[C0_I64]] : i64
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// CHECK: %[[T10:.*]] = arith.select %[[T9]], %[[T7]], %[[T8]] : i64
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// CHECK: %[[C0_I64_0:.*]] = arith.constant 0 : i64
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// CHECK: %[[T11:.*]] = arith.subi %[[C0_I64_0]], %[[T4]] : i64
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// CHECK: %[[T12:.*]] = arith.maxsi %[[T11]], %[[T1]] : i64
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// CHECK: %[[T13:.*]] = arith.minsi %[[T4]], %[[T12]] : i64
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// CHECK: %[[T14:.*]] = arith.addi %[[T4]], %[[T13]] : i64
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// CHECK: %[[T15:.*]] = arith.cmpi sge, %[[T13]], %[[C0_I64_0]] : i64
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// CHECK: %[[T16:.*]] = arith.select %[[T15]], %[[T13]], %[[T14]] : i64
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// CHECK: %[[C0:.*]] = arith.constant 0 : index
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// CHECK: %[[DIM_1:.*]] = tensor.dim %[[T0]], %[[C0]] : tensor<?x?x?xf32>
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// CHECK: %[[T17:.*]] = arith.index_cast %[[DIM_1]] : index to i64
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// CHECK: %[[C1_2:.*]] = arith.constant 1 : index
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// CHECK: %[[DIM_3:.*]] = tensor.dim %[[T0]], %[[C1_2]] : tensor<?x?x?xf32>
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// CHECK: %[[T18:.*]] = arith.index_cast %[[DIM_3]] : index to i64
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// CHECK: %[[C2:.*]] = arith.constant 2 : index
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// CHECK: %[[DIM_4:.*]] = tensor.dim %[[T0]], %[[C2]] : tensor<?x?x?xf32>
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// CHECK: %[[T19:.*]] = arith.index_cast %[[DIM_4]] : index to i64
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// CHECK: %[[C0_I64_5:.*]] = arith.constant 0 : i64
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// CHECK: %[[C1_I64:.*]] = arith.constant 1 : i64
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// CHECK: %[[T20:.*]] = arith.cmpi eq, %[[T16]], %[[C0_I64_5]] : i64
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// CHECK: %[[T21:.*]] = arith.select %[[T20]], %[[T18]], %[[T16]] : i64
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// CHECK: %[[FROM_ELEMENTS:.*]] = tensor.from_elements %[[C0_I64_5]], %[[T10]], %[[C0_I64_5]] : tensor<3xi64>
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// CHECK: %[[FROM_ELEMENTS_6:.*]] = tensor.from_elements %[[T17]], %[[T21]], %[[T19]] : tensor<3xi64>
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// CHECK: %[[FROM_ELEMENTS_7:.*]] = tensor.from_elements %[[C1_I64]], %[[T2]], %[[C1_I64]] : tensor<3xi64>
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// CHECK: %[[T22:.*]] = mhlo.real_dynamic_slice %[[T0]], %[[FROM_ELEMENTS]], %[[FROM_ELEMENTS]]_6, %[[FROM_ELEMENTS]]_7 : (tensor<?x?x?xf32>, tensor<3xi64>, tensor<3xi64>, tensor<3xi64>) -> tensor<?x1x?xf32>
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// CHECK: %[[T23:.*]] = torch_c.from_builtin_tensor %[[T22]] : tensor<?x1x?xf32> -> !torch.vtensor<[?,1,?],f32>
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// CHECK: return %[[T23]] : !torch.vtensor<[?,1,?],f32>
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func.func @torch.aten.slice.last$slice_like(%arg0: !torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[?,1,?],f32> {
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%int0 = torch.constant.int 0
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%int1 = torch.constant.int 1
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%int-1 = torch.constant.int -1
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%0 = torch.aten.slice.Tensor %arg0, %int1, %int-1, %int0, %int1 : !torch.vtensor<[?,?,?],f32>, !torch.int, !torch.int, !torch.int, !torch.int -> !torch.vtensor<[?,1,?],f32>
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return %0 : !torch.vtensor<[?,1,?],f32>
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}
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// -----
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// CHECK-LABEL: func.func @torch.aten.slice.last.static$slice_like(
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// CHECK-SAME: %[[ARG0:.*]]: !torch.vtensor<[4,65,256],f32>) -> !torch.vtensor<[4,1,256],f32> {
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// CHECK: %[[T0:.*]] = torch_c.to_builtin_tensor %[[ARG0]] : !torch.vtensor<[4,65,256],f32> -> tensor<4x65x256xf32>
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// CHECK: %[[INT0:.*]] = torch.constant.int 0
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// CHECK: %[[T1:.*]] = torch_c.to_i64 %[[INT0]]
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// CHECK: %[[INT1:.*]] = torch.constant.int 1
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// CHECK: %[[T2:.*]] = torch_c.to_i64 %[[INT1]]
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// CHECK: %[[INT:.*]]-1 = torch.constant.int -1
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// CHECK: %[[T3:.*]] = torch_c.to_i64 %[[INT]]-1
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// CHECK: %[[C1:.*]] = arith.constant 1 : index
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// CHECK: %[[DIM:.*]] = tensor.dim %[[T0]], %[[C1]] : tensor<4x65x256xf32>
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// CHECK: %[[T4:.*]] = arith.index_cast %[[DIM]] : index to i64
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// CHECK: %[[C0_I64:.*]] = arith.constant 0 : i64
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// CHECK: %[[T5:.*]] = arith.subi %[[C0_I64]], %[[T4]] : i64
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// CHECK: %[[T6:.*]] = arith.maxsi %[[T5]], %[[T3]] : i64
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// CHECK: %[[T7:.*]] = arith.minsi %[[T4]], %[[T6]] : i64
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// CHECK: %[[T8:.*]] = arith.addi %[[T4]], %[[T7]] : i64
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// CHECK: %[[T9:.*]] = arith.cmpi sge, %[[T7]], %[[C0_I64]] : i64
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// CHECK: %[[T10:.*]] = arith.select %[[T9]], %[[T7]], %[[T8]] : i64
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// CHECK: %[[C0_I64_0:.*]] = arith.constant 0 : i64
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// CHECK: %[[T11:.*]] = arith.subi %[[C0_I64_0]], %[[T4]] : i64
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// CHECK: %[[T12:.*]] = arith.maxsi %[[T11]], %[[T1]] : i64
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// CHECK: %[[T13:.*]] = arith.minsi %[[T4]], %[[T12]] : i64
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// CHECK: %[[T14:.*]] = arith.addi %[[T4]], %[[T13]] : i64
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// CHECK: %[[T15:.*]] = arith.cmpi sge, %[[T13]], %[[C0_I64_0]] : i64
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// CHECK: %[[T16:.*]] = arith.select %[[T15]], %[[T13]], %[[T14]] : i64
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// CHECK: %[[C0:.*]] = arith.constant 0 : index
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// CHECK: %[[DIM_1:.*]] = tensor.dim %[[T0]], %[[C0]] : tensor<4x65x256xf32>
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// CHECK: %[[T17:.*]] = arith.index_cast %[[DIM_1]] : index to i64
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// CHECK: %[[C1_2:.*]] = arith.constant 1 : index
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// CHECK: %[[DIM_3:.*]] = tensor.dim %[[T0]], %[[C1_2]] : tensor<4x65x256xf32>
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// CHECK: %[[T18:.*]] = arith.index_cast %[[DIM_3]] : index to i64
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// CHECK: %[[C2:.*]] = arith.constant 2 : index
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// CHECK: %[[DIM_4:.*]] = tensor.dim %[[T0]], %[[C2]] : tensor<4x65x256xf32>
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// CHECK: %[[T19:.*]] = arith.index_cast %[[DIM_4]] : index to i64
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// CHECK: %[[C0_I64_5:.*]] = arith.constant 0 : i64
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// CHECK: %[[C1_I64:.*]] = arith.constant 1 : i64
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// CHECK: %[[T20:.*]] = arith.cmpi eq, %[[T16]], %[[C0_I64_5]] : i64
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// CHECK: %[[T21:.*]] = arith.select %[[T20]], %[[T18]], %[[T16]] : i64
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// CHECK: %[[FROM_ELEMENTS:.*]] = tensor.from_elements %[[C0_I64_5]], %[[T10]], %[[C0_I64_5]] : tensor<3xi64>
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// CHECK: %[[FROM_ELEMENTS_6:.*]] = tensor.from_elements %[[T17]], %[[T21]], %[[T19]] : tensor<3xi64>
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// CHECK: %[[FROM_ELEMENTS_7:.*]] = tensor.from_elements %[[C1_I64]], %[[T2]], %[[C1_I64]] : tensor<3xi64>
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// CHECK: %[[T22:.*]] = mhlo.real_dynamic_slice %[[T0]], %[[FROM_ELEMENTS]], %[[FROM_ELEMENTS]]_6, %[[FROM_ELEMENTS]]_7 : (tensor<4x65x256xf32>, tensor<3xi64>, tensor<3xi64>, tensor<3xi64>) -> tensor<4x1x256xf32>
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// CHECK: %[[T23:.*]] = torch_c.from_builtin_tensor %[[T22]] : tensor<4x1x256xf32> -> !torch.vtensor<[4,1,256],f32>
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// CHECK: return %[[T23]] : !torch.vtensor<[4,1,256],f32>
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|
func.func @torch.aten.slice.last.static$slice_like(%arg0: !torch.vtensor<[4,65,256],f32>) -> !torch.vtensor<[4,1,256],f32> {
|
|
%int0 = torch.constant.int 0
|
|
%int1 = torch.constant.int 1
|
|
%int-1 = torch.constant.int -1
|
|
%0 = torch.aten.slice.Tensor %arg0, %int1, %int-1, %int0, %int1 : !torch.vtensor<[4,65,256],f32>, !torch.int, !torch.int, !torch.int, !torch.int -> !torch.vtensor<[4,1,256],f32>
|
|
return %0 : !torch.vtensor<[4,1,256],f32>
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: func.func @torch.aten.slice.none$slice_like(
|
|
// CHECK-SAME: %[[ARG0:.*]]: !torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[?,?,?],f32> {
|
|
// CHECK: %[[T0:.*]] = torch_c.to_builtin_tensor %[[ARG0]] : !torch.vtensor<[?,?,?],f32> -> tensor<?x?x?xf32>
|
|
// CHECK: %[[INT1:.*]] = torch.constant.int 1
|
|
// CHECK: %[[INT2:.*]] = torch.constant.int 2
|
|
// CHECK: %[[T1:.*]] = torch_c.to_i64 %[[INT2]]
|
|
// CHECK: %[[NONE:.*]] = torch.constant.none
|
|
// CHECK: %[[C1:.*]] = arith.constant 1 : index
|
|
// CHECK: %[[DIM:.*]] = tensor.dim %[[T0]], %[[C1]] : tensor<?x?x?xf32>
|
|
// CHECK: %[[T2:.*]] = arith.index_cast %[[DIM]] : index to i64
|
|
// CHECK: %[[C0_I64:.*]] = arith.constant 0 : i64
|
|
// CHECK: %[[C0:.*]] = arith.constant 0 : index
|
|
// CHECK: %[[DIM_0:.*]] = tensor.dim %[[T0]], %[[C0]] : tensor<?x?x?xf32>
|
|
// CHECK: %[[T3:.*]] = arith.index_cast %[[DIM_0]] : index to i64
|
|
// CHECK: %[[C1_1:.*]] = arith.constant 1 : index
|
|
// CHECK: %[[DIM_2:.*]] = tensor.dim %[[T0]], %[[C1_1]] : tensor<?x?x?xf32>
|
|
// CHECK: %[[T4:.*]] = arith.index_cast %[[DIM_2]] : index to i64
|
|
// CHECK: %[[C2:.*]] = arith.constant 2 : index
|
|
// CHECK: %[[DIM_3:.*]] = tensor.dim %[[T0]], %[[C2]] : tensor<?x?x?xf32>
|
|
// CHECK: %[[T5:.*]] = arith.index_cast %[[DIM_3]] : index to i64
|
|
// CHECK: %[[C0_I64_4:.*]] = arith.constant 0 : i64
|
|
// CHECK: %[[C1_I64:.*]] = arith.constant 1 : i64
|
|
// CHECK: %[[T6:.*]] = arith.cmpi eq, %[[T2]], %[[C0_I64_4]] : i64
|
|
// CHECK: %[[T7:.*]] = arith.select %[[T6]], %[[T4]], %[[T2]] : i64
|
|
// CHECK: %[[FROM_ELEMENTS:.*]] = tensor.from_elements %[[C0_I64_4]], %[[C0_I64]], %[[C0_I64_4]] : tensor<3xi64>
|
|
// CHECK: %[[FROM_ELEMENTS_5:.*]] = tensor.from_elements %[[T3]], %[[T7]], %[[T5]] : tensor<3xi64>
|
|
// CHECK: %[[FROM_ELEMENTS_6:.*]] = tensor.from_elements %[[C1_I64]], %[[T1]], %[[C1_I64]] : tensor<3xi64>
|
|
// CHECK: %[[T8:.*]] = mhlo.real_dynamic_slice %[[T0]], %[[FROM_ELEMENTS]], %[[FROM_ELEMENTS]]_5, %[[FROM_ELEMENTS]]_6 : (tensor<?x?x?xf32>, tensor<3xi64>, tensor<3xi64>, tensor<3xi64>) -> tensor<?x?x?xf32>
|
|
// CHECK: %[[T9:.*]] = torch_c.from_builtin_tensor %[[T8]] : tensor<?x?x?xf32> -> !torch.vtensor<[?,?,?],f32>
|
|
// CHECK: return %[[T9]] : !torch.vtensor<[?,?,?],f32>
|
|
func.func @torch.aten.slice.none$slice_like(%arg0: !torch.vtensor<[?,?,?],f32>) -> !torch.vtensor<[?,?,?],f32> {
|
|
%int1 = torch.constant.int 1
|
|
%int2 = torch.constant.int 2
|
|
%none = torch.constant.none
|
|
%0 = torch.aten.slice.Tensor %arg0, %int1, %none, %none, %int2 : !torch.vtensor<[?,?,?],f32>, !torch.int, !torch.none, !torch.none, !torch.int -> !torch.vtensor<[?,?,?],f32>
|
|
return %0 : !torch.vtensor<[?,?,?],f32>
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: func.func @torch.aten.slice.none.static$slice_like(
|
|
// CHECK-SAME: %[[ARG0:.*]]: !torch.vtensor<[4,65,256],f32>) -> !torch.vtensor<[4,33,256],f32> {
|
|
// CHECK: %[[T0:.*]] = torch_c.to_builtin_tensor %[[ARG0]] : !torch.vtensor<[4,65,256],f32> -> tensor<4x65x256xf32>
|
|
// CHECK: %[[INT1:.*]] = torch.constant.int 1
|
|
// CHECK: %[[INT2:.*]] = torch.constant.int 2
|
|
// CHECK: %[[T1:.*]] = torch_c.to_i64 %[[INT2]]
|
|
// CHECK: %[[NONE:.*]] = torch.constant.none
|
|
// CHECK: %[[C1:.*]] = arith.constant 1 : index
|
|
// CHECK: %[[DIM:.*]] = tensor.dim %[[T0]], %[[C1]] : tensor<4x65x256xf32>
|
|
// CHECK: %[[T2:.*]] = arith.index_cast %[[DIM]] : index to i64
|
|
// CHECK: %[[C0_I64:.*]] = arith.constant 0 : i64
|
|
// CHECK: %[[C0:.*]] = arith.constant 0 : index
|
|
// CHECK: %[[DIM_0:.*]] = tensor.dim %[[T0]], %[[C0]] : tensor<4x65x256xf32>
|
|
// CHECK: %[[T3:.*]] = arith.index_cast %[[DIM_0]] : index to i64
|
|
// CHECK: %[[C1_1:.*]] = arith.constant 1 : index
|
|
// CHECK: %[[DIM_2:.*]] = tensor.dim %[[T0]], %[[C1_1]] : tensor<4x65x256xf32>
|
|
// CHECK: %[[T4:.*]] = arith.index_cast %[[DIM_2]] : index to i64
|
|
// CHECK: %[[C2:.*]] = arith.constant 2 : index
|
|
// CHECK: %[[DIM_3:.*]] = tensor.dim %[[T0]], %[[C2]] : tensor<4x65x256xf32>
|
|
// CHECK: %[[T5:.*]] = arith.index_cast %[[DIM_3]] : index to i64
|
|
// CHECK: %[[C0_I64_4:.*]] = arith.constant 0 : i64
|
|
// CHECK: %[[C1_I64:.*]] = arith.constant 1 : i64
|
|
// CHECK: %[[T6:.*]] = arith.cmpi eq, %[[T2]], %[[C0_I64_4]] : i64
|
|
// CHECK: %[[T7:.*]] = arith.select %[[T6]], %[[T4]], %[[T2]] : i64
|
|
// CHECK: %[[FROM_ELEMENTS:.*]] = tensor.from_elements %[[C0_I64_4]], %[[C0_I64]], %[[C0_I64_4]] : tensor<3xi64>
|
|
// CHECK: %[[FROM_ELEMENTS_5:.*]] = tensor.from_elements %[[T3]], %[[T7]], %[[T5]] : tensor<3xi64>
|
|
// CHECK: %[[FROM_ELEMENTS_6:.*]] = tensor.from_elements %[[C1_I64]], %[[T1]], %[[C1_I64]] : tensor<3xi64>
|
|
// CHECK: %[[T8:.*]] = mhlo.real_dynamic_slice %[[T0]], %[[FROM_ELEMENTS]], %[[FROM_ELEMENTS]]_5, %[[FROM_ELEMENTS]]_6 : (tensor<4x65x256xf32>, tensor<3xi64>, tensor<3xi64>, tensor<3xi64>) -> tensor<4x33x256xf32>
|
|
// CHECK: %[[T9:.*]] = torch_c.from_builtin_tensor %[[T8]] : tensor<4x33x256xf32> -> !torch.vtensor<[4,33,256],f32>
|
|
// CHECK: return %[[T9]] : !torch.vtensor<[4,33,256],f32>
|
|
func.func @torch.aten.slice.none.static$slice_like(%arg0: !torch.vtensor<[4,65,256],f32>) -> !torch.vtensor<[4,33,256],f32> {
|
|
%int1 = torch.constant.int 1
|
|
%int2 = torch.constant.int 2
|
|
%none = torch.constant.none
|
|
%0 = torch.aten.slice.Tensor %arg0, %int1, %none, %none, %int2 : !torch.vtensor<[4,65,256],f32>, !torch.int, !torch.none, !torch.none, !torch.int -> !torch.vtensor<[4,33,256],f32>
|
|
return %0 : !torch.vtensor<[4,33,256],f32>
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: func.func @torch.aten.view$basic(
|
|
// CHECK-SAME: %[[ARG0:.*]]: !torch.vtensor<[?,?,?,?],f32>) -> !torch.vtensor<[?,224],f32> {
|
|
// CHECK: %[[T0:.*]] = torch_c.to_builtin_tensor %[[ARG0]] : !torch.vtensor<[?,?,?,?],f32> -> tensor<?x?x?x?xf32>
|
|
// CHECK: %[[INT:.*]]-1 = torch.constant.int -1
|
|
// CHECK: %[[INT224:.*]] = torch.constant.int 224
|
|
// CHECK: %[[T1:.*]] = torch.prim.ListConstruct %[[INT]]-1, %[[INT]]224 : (!torch.int, !torch.int) -> !torch.list<int>
|
|
// CHECK: %[[T2:.*]] = torch_c.to_i64 %[[INT]]-1
|
|
// CHECK: %[[T3:.*]] = torch_c.to_i64 %[[INT224]]
|
|
// CHECK: %[[C1_I64:.*]] = arith.constant 1 : i64
|
|
// CHECK: %[[T4:.*]] = arith.muli %[[C1_I64]], %[[T2]] : i64
|
|
// CHECK: %[[T5:.*]] = arith.muli %[[T4]], %[[T3]] : i64
|
|
// CHECK: %[[T6:.*]] = arith.index_cast %[[T5]] : i64 to index
|
|
// CHECK: %[[FROM_ELEMENTS:.*]] = tensor.from_elements %[[T2]], %[[T3]] : tensor<2xi64>
|
|
// CHECK: %[[T7:.*]] = mhlo.compute_reshape_shape %[[T6]], %[[FROM_ELEMENTS]] : (index, tensor<2xi64>) -> tensor<2xi64>
|
|
// CHECK: %[[T8:.*]] = mhlo.dynamic_reshape %[[T0]], %[[T7]] : (tensor<?x?x?x?xf32>, tensor<2xi64>) -> tensor<?x224xf32>
|
|
// CHECK: %[[T9:.*]] = torch_c.from_builtin_tensor %[[T8]] : tensor<?x224xf32> -> !torch.vtensor<[?,224],f32>
|
|
// CHECK: return %[[T9]] : !torch.vtensor<[?,224],f32>
|
|
func.func @torch.aten.view$basic(%arg0: !torch.vtensor<[?,?,?,?],f32>) -> !torch.vtensor<[?,224],f32> {
|
|
%int-1 = torch.constant.int -1
|
|
%int224 = torch.constant.int 224
|
|
%0 = torch.prim.ListConstruct %int-1, %int224 : (!torch.int, !torch.int) -> !torch.list<int>
|
|
%1 = torch.aten.view %arg0, %0 : !torch.vtensor<[?,?,?,?],f32>, !torch.list<int> -> !torch.vtensor<[?,224],f32>
|
|
return %1 : !torch.vtensor<[?,224],f32>
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: func.func @torch.aten.reshape$basic(
|
|
// CHECK-SAME: %[[ARG0:.*]]: !torch.vtensor<[?,?,?,?,?],f32>) -> !torch.vtensor<[?,120,4,64],f32> {
|
|
// CHECK: %[[T0:.*]] = torch_c.to_builtin_tensor %[[ARG0]] : !torch.vtensor<[?,?,?,?,?],f32> -> tensor<?x?x?x?x?xf32>
|
|
// CHECK: %[[INT:.*]]-1 = torch.constant.int -1
|
|
// CHECK: %[[INT120:.*]] = torch.constant.int 120
|
|
// CHECK: %[[INT4:.*]] = torch.constant.int 4
|
|
// CHECK: %[[INT64:.*]] = torch.constant.int 64
|
|
// CHECK: %[[T1:.*]] = torch.prim.ListConstruct %[[INT]]-1, %[[INT]]120, %[[INT]]4, %[[INT]]64 : (!torch.int, !torch.int, !torch.int, !torch.int) -> !torch.list<int>
|
|
// CHECK: %[[T2:.*]] = torch_c.to_i64 %[[INT]]-1
|
|
// CHECK: %[[T3:.*]] = torch_c.to_i64 %[[INT120]]
|
|
// CHECK: %[[T4:.*]] = torch_c.to_i64 %[[INT4]]
|
|
// CHECK: %[[T5:.*]] = torch_c.to_i64 %[[INT64]]
|
|
// CHECK: %[[C1_I64:.*]] = arith.constant 1 : i64
|
|
// CHECK: %[[T6:.*]] = arith.muli %[[C1_I64]], %[[T2]] : i64
|
|
// CHECK: %[[T7:.*]] = arith.muli %[[T6]], %[[T3]] : i64
|
|
// CHECK: %[[T8:.*]] = arith.muli %[[T7]], %[[T4]] : i64
|
|
// CHECK: %[[T9:.*]] = arith.muli %[[T8]], %[[T5]] : i64
|
|
// CHECK: %[[T10:.*]] = arith.index_cast %[[T9]] : i64 to index
|
|
// CHECK: %[[FROM_ELEMENTS:.*]] = tensor.from_elements %[[T2]], %[[T3]], %[[T4]], %[[T5]] : tensor<4xi64>
|
|
// CHECK: %[[T11:.*]] = mhlo.compute_reshape_shape %[[T10]], %[[FROM_ELEMENTS]] : (index, tensor<4xi64>) -> tensor<4xi64>
|
|
// CHECK: %[[T12:.*]] = mhlo.dynamic_reshape %[[T0]], %[[T11]] : (tensor<?x?x?x?x?xf32>, tensor<4xi64>) -> tensor<?x120x4x64xf32>
|
|
// CHECK: %[[T13:.*]] = torch_c.from_builtin_tensor %[[T12]] : tensor<?x120x4x64xf32> -> !torch.vtensor<[?,120,4,64],f32>
|
|
// CHECK: return %[[T13]] : !torch.vtensor<[?,120,4,64],f32>
|
|
func.func @torch.aten.reshape$basic(%arg0: !torch.vtensor<[?,?,?,?,?],f32>) -> !torch.vtensor<[?,120,4,64],f32> {
|
|
%int-1 = torch.constant.int -1
|
|
%int120 = torch.constant.int 120
|
|
%int4 = torch.constant.int 4
|
|
%int64 = torch.constant.int 64
|
|
%0 = torch.prim.ListConstruct %int-1, %int120, %int4, %int64 : (!torch.int, !torch.int, !torch.int, !torch.int) -> !torch.list<int>
|
|
%1 = torch.aten.reshape %arg0, %0 : !torch.vtensor<[?,?,?,?,?],f32>, !torch.list<int> -> !torch.vtensor<[?,120,4,64],f32>
|
|
return %1 : !torch.vtensor<[?,120,4,64],f32>
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: func.func @torch.aten.view$to_rank1(
|
|
// CHECK-SAME: %[[ARG0:.*]]: !torch.vtensor<[],f32>) -> !torch.vtensor<[1],f32> {
|
|
// CHECK: %[[T0:.*]] = torch_c.to_builtin_tensor %[[ARG0]] : !torch.vtensor<[],f32> -> tensor<f32>
|
|
// CHECK: %[[INT1:.*]] = torch.constant.int 1
|
|
// CHECK: %[[T1:.*]] = torch.prim.ListConstruct %[[INT1]] : (!torch.int) -> !torch.list<int>
|
|
// CHECK: %[[T2:.*]] = mhlo.reshape %[[T0]] : (tensor<f32>) -> tensor<1xf32>
|
|
// CHECK: %[[T3:.*]] = torch_c.from_builtin_tensor %[[T2]] : tensor<1xf32> -> !torch.vtensor<[1],f32>
|
|
// CHECK: return %[[T3]] : !torch.vtensor<[1],f32>
|
|
func.func @torch.aten.view$to_rank1(%arg0: !torch.vtensor<[],f32>) -> !torch.vtensor<[1],f32> {
|
|
%int1 = torch.constant.int 1
|
|
%0 = torch.prim.ListConstruct %int1 : (!torch.int) -> !torch.list<int>
|
|
%1 = torch.aten.view %arg0, %0 : !torch.vtensor<[],f32>, !torch.list<int> -> !torch.vtensor<[1],f32>
|
|
return %1 : !torch.vtensor<[1],f32>
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: func.func @torch.aten.view$to_rank0(
|
|
// CHECK-SAME: %[[ARG0:.*]]: !torch.vtensor<[1],f32>) -> !torch.vtensor<[],f32> {
|
|
// CHECK: %[[T0:.*]] = torch_c.to_builtin_tensor %[[ARG0]] : !torch.vtensor<[1],f32> -> tensor<1xf32>
|
|
// CHECK: %[[T1:.*]] = torch.prim.ListConstruct : () -> !torch.list<int>
|
|
// CHECK: %[[T2:.*]] = mhlo.reshape %[[T0]] : (tensor<1xf32>) -> tensor<f32>
|
|
// CHECK: %[[T3:.*]] = torch_c.from_builtin_tensor %[[T2]] : tensor<f32> -> !torch.vtensor<[],f32>
|
|
// CHECK: return %[[T3]] : !torch.vtensor<[],f32>
|
|
func.func @torch.aten.view$to_rank0(%arg0: !torch.vtensor<[1],f32>) -> !torch.vtensor<[],f32> {
|
|
%0 = torch.prim.ListConstruct : () -> !torch.list<int>
|
|
%1 = torch.aten.view %arg0, %0 : !torch.vtensor<[1],f32>, !torch.list<int> -> !torch.vtensor<[],f32>
|
|
return %1 : !torch.vtensor<[],f32>
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: func.func @torch.aten.squeeze.dim$0$static(
|
|
// CHECK-SAME: %[[ARG0:.*]]: !torch.vtensor<[2,1,2,1,2],f32>) -> !torch.vtensor<[2,1,2,1,2],f32> {
|
|
// CHECK: %[[T0:.*]] = torch_c.to_builtin_tensor %[[ARG0]] : !torch.vtensor<[2,1,2,1,2],f32> -> tensor<2x1x2x1x2xf32>
|
|
// CHECK: %[[INT0:.*]] = torch.constant.int 0
|
|
// CHECK: %[[T1:.*]] = torch_c.from_builtin_tensor %[[T0]] : tensor<2x1x2x1x2xf32> -> !torch.vtensor<[2,1,2,1,2],f32>
|
|
// CHECK: return %[[T1]] : !torch.vtensor<[2,1,2,1,2],f32>
|
|
func.func @torch.aten.squeeze.dim$0$static(%arg0: !torch.vtensor<[2,1,2,1,2],f32>) -> !torch.vtensor<[2,1,2,1,2],f32> {
|
|
%int0 = torch.constant.int 0
|
|
%0 = torch.aten.squeeze.dim %arg0, %int0 : !torch.vtensor<[2,1,2,1,2],f32>, !torch.int -> !torch.vtensor<[2,1,2,1,2],f32>
|
|
return %0 : !torch.vtensor<[2,1,2,1,2],f32>
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: func.func @torch.aten.squeeze.dim$1(
|
|
// CHECK-SAME: %[[ARG0:.*]]: !torch.vtensor<[?,1,?,1,?],f32>) -> !torch.vtensor<[?,?,1,?],f32> {
|
|
// CHECK: %[[T0:.*]] = torch_c.to_builtin_tensor %[[ARG0]] : !torch.vtensor<[?,1,?,1,?],f32> -> tensor<?x1x?x1x?xf32>
|
|
// CHECK: %[[INT1:.*]] = torch.constant.int 1
|
|
// CHECK: %[[C0:.*]] = arith.constant 0 : index
|
|
// CHECK: %[[DIM:.*]] = tensor.dim %[[T0]], %[[C0]] : tensor<?x1x?x1x?xf32>
|
|
// CHECK: %[[T1:.*]] = arith.index_cast %[[DIM]] : index to i64
|
|
// CHECK: %[[C2:.*]] = arith.constant 2 : index
|
|
// CHECK: %[[DIM_0:.*]] = tensor.dim %[[T0]], %[[C2]] : tensor<?x1x?x1x?xf32>
|
|
// CHECK: %[[T2:.*]] = arith.index_cast %[[DIM_0]] : index to i64
|
|
// CHECK: %[[C3:.*]] = arith.constant 3 : index
|
|
// CHECK: %[[DIM_1:.*]] = tensor.dim %[[T0]], %[[C3]] : tensor<?x1x?x1x?xf32>
|
|
// CHECK: %[[T3:.*]] = arith.index_cast %[[DIM_1]] : index to i64
|
|
// CHECK: %[[C4:.*]] = arith.constant 4 : index
|
|
// CHECK: %[[DIM_2:.*]] = tensor.dim %[[T0]], %[[C4]] : tensor<?x1x?x1x?xf32>
|
|
// CHECK: %[[T4:.*]] = arith.index_cast %[[DIM_2]] : index to i64
|
|
// CHECK: %[[FROM_ELEMENTS:.*]] = tensor.from_elements %[[T1]], %[[T2]], %[[T3]], %[[T4]] : tensor<4xi64>
|
|
// CHECK: %[[T5:.*]] = mhlo.dynamic_reshape %[[T0]], %[[FROM_ELEMENTS]] : (tensor<?x1x?x1x?xf32>, tensor<4xi64>) -> tensor<?x?x1x?xf32>
|
|
// CHECK: %[[T6:.*]] = torch_c.from_builtin_tensor %[[T5]] : tensor<?x?x1x?xf32> -> !torch.vtensor<[?,?,1,?],f32>
|
|
// CHECK: return %[[T6]] : !torch.vtensor<[?,?,1,?],f32>
|
|
func.func @torch.aten.squeeze.dim$1(%arg0: !torch.vtensor<[?,1,?,1,?],f32>) -> !torch.vtensor<[?,?,1,?],f32> {
|
|
%int1 = torch.constant.int 1
|
|
%0 = torch.aten.squeeze.dim %arg0, %int1 : !torch.vtensor<[?,1,?,1,?],f32>, !torch.int -> !torch.vtensor<[?,?,1,?],f32>
|
|
return %0 : !torch.vtensor<[?,?,1,?],f32>
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: func.func @torch.aten.squeeze.dim$from_end(
|
|
// CHECK-SAME: %[[ARG0:.*]]: !torch.vtensor<[?,1,?,1,?],f32>) -> !torch.vtensor<[?,1,?,?],f32> {
|
|
// CHECK: %[[T0:.*]] = torch_c.to_builtin_tensor %[[ARG0]] : !torch.vtensor<[?,1,?,1,?],f32> -> tensor<?x1x?x1x?xf32>
|
|
// CHECK: %[[INT:.*]]-2 = torch.constant.int -2
|
|
// CHECK: %[[C0:.*]] = arith.constant 0 : index
|
|
// CHECK: %[[DIM:.*]] = tensor.dim %[[T0]], %[[C0]] : tensor<?x1x?x1x?xf32>
|
|
// CHECK: %[[T1:.*]] = arith.index_cast %[[DIM]] : index to i64
|
|
// CHECK: %[[C1:.*]] = arith.constant 1 : index
|
|
// CHECK: %[[DIM_0:.*]] = tensor.dim %[[T0]], %[[C1]] : tensor<?x1x?x1x?xf32>
|
|
// CHECK: %[[T2:.*]] = arith.index_cast %[[DIM_0]] : index to i64
|
|
// CHECK: %[[C2:.*]] = arith.constant 2 : index
|
|
// CHECK: %[[DIM_1:.*]] = tensor.dim %[[T0]], %[[C2]] : tensor<?x1x?x1x?xf32>
|
|
// CHECK: %[[T3:.*]] = arith.index_cast %[[DIM_1]] : index to i64
|
|
// CHECK: %[[C4:.*]] = arith.constant 4 : index
|
|
// CHECK: %[[DIM_2:.*]] = tensor.dim %[[T0]], %[[C4]] : tensor<?x1x?x1x?xf32>
|
|
// CHECK: %[[T4:.*]] = arith.index_cast %[[DIM_2]] : index to i64
|
|
// CHECK: %[[FROM_ELEMENTS:.*]] = tensor.from_elements %[[T1]], %[[T2]], %[[T3]], %[[T4]] : tensor<4xi64>
|
|
// CHECK: %[[T5:.*]] = mhlo.dynamic_reshape %[[T0]], %[[FROM_ELEMENTS]] : (tensor<?x1x?x1x?xf32>, tensor<4xi64>) -> tensor<?x1x?x?xf32>
|
|
// CHECK: %[[T6:.*]] = torch_c.from_builtin_tensor %[[T5]] : tensor<?x1x?x?xf32> -> !torch.vtensor<[?,1,?,?],f32>
|
|
// CHECK: return %[[T6]] : !torch.vtensor<[?,1,?,?],f32>
|
|
func.func @torch.aten.squeeze.dim$from_end(%arg0: !torch.vtensor<[?,1,?,1,?],f32>) -> !torch.vtensor<[?,1,?,?],f32> {
|
|
%int-2 = torch.constant.int -2
|
|
%0 = torch.aten.squeeze.dim %arg0, %int-2 : !torch.vtensor<[?,1,?,1,?],f32>, !torch.int -> !torch.vtensor<[?,1,?,?],f32>
|
|
return %0 : !torch.vtensor<[?,1,?,?],f32>
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: func.func @torch.aten.squeeze$static(
|
|
// CHECK-SAME: %[[ARG0:.*]]: !torch.vtensor<[2,1,2,1,2],f32>) -> !torch.vtensor<[2,2,2],f32> {
|
|
// CHECK: %[[T0:.*]] = torch_c.to_builtin_tensor %[[ARG0]] : !torch.vtensor<[2,1,2,1,2],f32> -> tensor<2x1x2x1x2xf32>
|
|
// CHECK: %[[C0:.*]] = arith.constant 0 : index
|
|
// CHECK: %[[DIM:.*]] = tensor.dim %[[T0]], %[[C0]] : tensor<2x1x2x1x2xf32>
|
|
// CHECK: %[[T1:.*]] = arith.index_cast %[[DIM]] : index to i64
|
|
// CHECK: %[[C2:.*]] = arith.constant 2 : index
|
|
// CHECK: %[[DIM_0:.*]] = tensor.dim %[[T0]], %[[C2]] : tensor<2x1x2x1x2xf32>
|
|
// CHECK: %[[T2:.*]] = arith.index_cast %[[DIM_0]] : index to i64
|
|
// CHECK: %[[C4:.*]] = arith.constant 4 : index
|
|
// CHECK: %[[DIM_1:.*]] = tensor.dim %[[T0]], %[[C4]] : tensor<2x1x2x1x2xf32>
|
|
// CHECK: %[[T3:.*]] = arith.index_cast %[[DIM_1]] : index to i64
|
|
// CHECK: %[[FROM_ELEMENTS:.*]] = tensor.from_elements %[[T1]], %[[T2]], %[[T3]] : tensor<3xi64>
|
|
// CHECK: %[[T4:.*]] = mhlo.dynamic_reshape %[[T0]], %[[FROM_ELEMENTS]] : (tensor<2x1x2x1x2xf32>, tensor<3xi64>) -> tensor<2x2x2xf32>
|
|
// CHECK: %[[T5:.*]] = torch_c.from_builtin_tensor %[[T4]] : tensor<2x2x2xf32> -> !torch.vtensor<[2,2,2],f32>
|
|
// CHECK: return %[[T5]] : !torch.vtensor<[2,2,2],f32>
|
|
func.func @torch.aten.squeeze$static(%arg0: !torch.vtensor<[2,1,2,1,2],f32>) -> !torch.vtensor<[2,2,2],f32> {
|
|
%0 = torch.aten.squeeze %arg0 : !torch.vtensor<[2,1,2,1,2],f32> -> !torch.vtensor<[2,2,2],f32>
|
|
return %0 : !torch.vtensor<[2,2,2],f32>
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: func.func @torch.aten.unsqueeze$dim$0(
|
|
// CHECK-SAME: %[[ARG0:.*]]: !torch.vtensor<[?,?,?,?],f32>) -> !torch.vtensor<[1,?,?,?,?],f32> {
|
|
// CHECK: %[[T0:.*]] = torch_c.to_builtin_tensor %[[ARG0]] : !torch.vtensor<[?,?,?,?],f32> -> tensor<?x?x?x?xf32>
|
|
// CHECK: %[[INT0:.*]] = torch.constant.int 0
|
|
// CHECK: %[[C0:.*]] = arith.constant 0 : index
|
|
// CHECK: %[[DIM:.*]] = tensor.dim %[[T0]], %[[C0]] : tensor<?x?x?x?xf32>
|
|
// CHECK: %[[T1:.*]] = arith.index_cast %[[DIM]] : index to i64
|
|
// CHECK: %[[C1:.*]] = arith.constant 1 : index
|
|
// CHECK: %[[DIM_0:.*]] = tensor.dim %[[T0]], %[[C1]] : tensor<?x?x?x?xf32>
|
|
// CHECK: %[[T2:.*]] = arith.index_cast %[[DIM_0]] : index to i64
|
|
// CHECK: %[[C2:.*]] = arith.constant 2 : index
|
|
// CHECK: %[[DIM_1:.*]] = tensor.dim %[[T0]], %[[C2]] : tensor<?x?x?x?xf32>
|
|
// CHECK: %[[T3:.*]] = arith.index_cast %[[DIM_1]] : index to i64
|
|
// CHECK: %[[C3:.*]] = arith.constant 3 : index
|
|
// CHECK: %[[DIM_2:.*]] = tensor.dim %[[T0]], %[[C3]] : tensor<?x?x?x?xf32>
|
|
// CHECK: %[[T4:.*]] = arith.index_cast %[[DIM_2]] : index to i64
|
|
// CHECK: %[[C1_I64:.*]] = arith.constant 1 : i64
|
|
// CHECK: %[[FROM_ELEMENTS:.*]] = tensor.from_elements %[[C1_I64]], %[[T1]], %[[T2]], %[[T3]], %[[T4]] : tensor<5xi64>
|
|
// CHECK: %[[T5:.*]] = mhlo.dynamic_reshape %[[T0]], %[[FROM_ELEMENTS]] : (tensor<?x?x?x?xf32>, tensor<5xi64>) -> tensor<1x?x?x?x?xf32>
|
|
// CHECK: %[[T6:.*]] = torch_c.from_builtin_tensor %[[T5]] : tensor<1x?x?x?x?xf32> -> !torch.vtensor<[1,?,?,?,?],f32>
|
|
// CHECK: return %[[T6]] : !torch.vtensor<[1,?,?,?,?],f32>
|
|
func.func @torch.aten.unsqueeze$dim$0(%arg0: !torch.vtensor<[?,?,?,?],f32>) -> !torch.vtensor<[1,?,?,?,?],f32> {
|
|
%int0 = torch.constant.int 0
|
|
%0 = torch.aten.unsqueeze %arg0, %int0 : !torch.vtensor<[?,?,?,?],f32>, !torch.int -> !torch.vtensor<[1,?,?,?,?],f32>
|
|
return %0 : !torch.vtensor<[1,?,?,?,?],f32>
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: func.func @torch.aten.unsqueeze$dim$1(
|
|
// CHECK-SAME: %[[ARG0:.*]]: !torch.vtensor<[?,?,?,?],f32>) -> !torch.vtensor<[?,1,?,?,?],f32> {
|
|
// CHECK: %[[T0:.*]] = torch_c.to_builtin_tensor %[[ARG0]] : !torch.vtensor<[?,?,?,?],f32> -> tensor<?x?x?x?xf32>
|
|
// CHECK: %[[INT1:.*]] = torch.constant.int 1
|
|
// CHECK: %[[C0:.*]] = arith.constant 0 : index
|
|
// CHECK: %[[DIM:.*]] = tensor.dim %[[T0]], %[[C0]] : tensor<?x?x?x?xf32>
|
|
// CHECK: %[[T1:.*]] = arith.index_cast %[[DIM]] : index to i64
|
|
// CHECK: %[[C1:.*]] = arith.constant 1 : index
|
|
// CHECK: %[[DIM_0:.*]] = tensor.dim %[[T0]], %[[C1]] : tensor<?x?x?x?xf32>
|
|
// CHECK: %[[T2:.*]] = arith.index_cast %[[DIM_0]] : index to i64
|
|
// CHECK: %[[C2:.*]] = arith.constant 2 : index
|
|
// CHECK: %[[DIM_1:.*]] = tensor.dim %[[T0]], %[[C2]] : tensor<?x?x?x?xf32>
|
|
// CHECK: %[[T3:.*]] = arith.index_cast %[[DIM_1]] : index to i64
|
|
// CHECK: %[[C3:.*]] = arith.constant 3 : index
|
|
// CHECK: %[[DIM_2:.*]] = tensor.dim %[[T0]], %[[C3]] : tensor<?x?x?x?xf32>
|
|
// CHECK: %[[T4:.*]] = arith.index_cast %[[DIM_2]] : index to i64
|
|
// CHECK: %[[C1_I64:.*]] = arith.constant 1 : i64
|
|
// CHECK: %[[FROM_ELEMENTS:.*]] = tensor.from_elements %[[T1]], %[[C1_I64]], %[[T2]], %[[T3]], %[[T4]] : tensor<5xi64>
|
|
// CHECK: %[[T5:.*]] = mhlo.dynamic_reshape %[[T0]], %[[FROM_ELEMENTS]] : (tensor<?x?x?x?xf32>, tensor<5xi64>) -> tensor<?x1x?x?x?xf32>
|
|
// CHECK: %[[T6:.*]] = torch_c.from_builtin_tensor %[[T5]] : tensor<?x1x?x?x?xf32> -> !torch.vtensor<[?,1,?,?,?],f32>
|
|
// CHECK: return %[[T6]] : !torch.vtensor<[?,1,?,?,?],f32>
|
|
func.func @torch.aten.unsqueeze$dim$1(%arg0: !torch.vtensor<[?,?,?,?],f32>) -> !torch.vtensor<[?,1,?,?,?],f32> {
|
|
%int1 = torch.constant.int 1
|
|
%0 = torch.aten.unsqueeze %arg0, %int1 : !torch.vtensor<[?,?,?,?],f32>, !torch.int -> !torch.vtensor<[?,1,?,?,?],f32>
|
|
return %0 : !torch.vtensor<[?,1,?,?,?],f32>
|
|
}
|
|
|
|
// -----
|
|
|
|
// CHECK-LABEL: func.func @torch.aten.unsqueeze$from_end(
|
|
// CHECK-SAME: %[[ARG0:.*]]: !torch.vtensor<[?,?,?,?],f32>) -> !torch.vtensor<[?,?,?,1,?],f32> {
|
|
// CHECK: %[[T0:.*]] = torch_c.to_builtin_tensor %[[ARG0]] : !torch.vtensor<[?,?,?,?],f32> -> tensor<?x?x?x?xf32>
|
|
// CHECK: %[[INT:.*]]-2 = torch.constant.int -2
|
|
// CHECK: %[[C0:.*]] = arith.constant 0 : index
|
|
// CHECK: %[[DIM:.*]] = tensor.dim %[[T0]], %[[C0]] : tensor<?x?x?x?xf32>
|
|
// CHECK: %[[T1:.*]] = arith.index_cast %[[DIM]] : index to i64
|
|
// CHECK: %[[C1:.*]] = arith.constant 1 : index
|
|
// CHECK: %[[DIM_0:.*]] = tensor.dim %[[T0]], %[[C1]] : tensor<?x?x?x?xf32>
|
|
// CHECK: %[[T2:.*]] = arith.index_cast %[[DIM_0]] : index to i64
|
|
// CHECK: %[[C2:.*]] = arith.constant 2 : index
|
|
// CHECK: %[[DIM_1:.*]] = tensor.dim %[[T0]], %[[C2]] : tensor<?x?x?x?xf32>
|
|
// CHECK: %[[T3:.*]] = arith.index_cast %[[DIM_1]] : index to i64
|
|
// CHECK: %[[C3:.*]] = arith.constant 3 : index
|
|
// CHECK: %[[DIM_2:.*]] = tensor.dim %[[T0]], %[[C3]] : tensor<?x?x?x?xf32>
|
|
// CHECK: %[[T4:.*]] = arith.index_cast %[[DIM_2]] : index to i64
|
|
// CHECK: %[[C1_I64:.*]] = arith.constant 1 : i64
|
|
// CHECK: %[[FROM_ELEMENTS:.*]] = tensor.from_elements %[[T1]], %[[T2]], %[[T3]], %[[C1_I64]], %[[T4]] : tensor<5xi64>
|
|
// CHECK: %[[T5:.*]] = mhlo.dynamic_reshape %[[T0]], %[[FROM_ELEMENTS]] : (tensor<?x?x?x?xf32>, tensor<5xi64>) -> tensor<?x?x?x1x?xf32>
|
|
// CHECK: %[[T6:.*]] = torch_c.from_builtin_tensor %[[T5]] : tensor<?x?x?x1x?xf32> -> !torch.vtensor<[?,?,?,1,?],f32>
|
|
// CHECK: return %[[T6]] : !torch.vtensor<[?,?,?,1,?],f32>
|
|
func.func @torch.aten.unsqueeze$from_end(%arg0: !torch.vtensor<[?,?,?,?],f32>) -> !torch.vtensor<[?,?,?,1,?],f32> {
|
|
%int-2 = torch.constant.int -2
|
|
%0 = torch.aten.unsqueeze %arg0, %int-2 : !torch.vtensor<[?,?,?,?],f32>, !torch.int -> !torch.vtensor<[?,?,?,1,?],f32>
|
|
return %0 : !torch.vtensor<[?,?,?,1,?],f32>
|
|
}
|
|
|