# Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. # See https://llvm.org/LICENSE.txt for license information. # SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception # Also available under a BSD-style license. See LICENSE. import torch from torch_mlir_e2e_test.torchscript.framework import TestUtils from torch_mlir_e2e_test.torchscript.registry import register_test_case from torch_mlir_e2e_test.torchscript.annotations import annotate_args, export # ============================================================================== class ZerosModuleDefaultDtype(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ]) def forward(self): return torch.zeros(3, 4) @register_test_case(module_factory=lambda: ZerosModuleDefaultDtype()) def ZerosModuleDefaultDtype_basic(module, tu: TestUtils): module.forward() class ZerosModuleInt2D(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ]) def forward(self): return torch.zeros(3, 4, dtype=torch.int64) @register_test_case(module_factory=lambda: ZerosModuleInt2D()) def ZerosModuleInt2D_basic(module, tu: TestUtils): module.forward() class ZerosModuleInt3D(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ]) def forward(self): return torch.zeros(3, 4, 5, dtype=torch.int64) @register_test_case(module_factory=lambda: ZerosModuleInt3D()) def ZerosModuleInt3D_basic(module, tu: TestUtils): module.forward() class ZerosModuleFloat2D(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ]) def forward(self): return torch.zeros(3, 4, dtype=torch.float32) @register_test_case(module_factory=lambda: ZerosModuleFloat2D()) def ZerosModuleFloat2D_basic(module, tu: TestUtils): module.forward() class ZerosModuleFloat3D(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ]) def forward(self): return torch.zeros(3, 4, 5, dtype=torch.float32) @register_test_case(module_factory=lambda: ZerosModuleFloat3D()) def ZerosModuleFloat3D_basic(module, tu: TestUtils): module.forward() class ZerosModuleFalsePinMemory(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ]) def forward(self): return torch.zeros(3, 4, dtype=torch.float32, pin_memory=False) @register_test_case(module_factory=lambda: ZerosModuleFalsePinMemory()) def ZerosModuleFalsePinMemory_basic(module, tu: TestUtils): module.forward() # ============================================================================== class OnesModuleDefaultDtype(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ]) def forward(self): return torch.ones(3, 4) @register_test_case(module_factory=lambda: OnesModuleDefaultDtype()) def OnesModuleDefaultDtype_basic(module, tu: TestUtils): module.forward() class OnesModuleInt(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ]) def forward(self): return torch.ones(3, 4, dtype=torch.int64) @register_test_case(module_factory=lambda: OnesModuleInt()) def OnesModuleInt_basic(module, tu: TestUtils): module.forward() class OnesModuleFloat(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ]) def forward(self): return torch.ones(3, 4, dtype=torch.float32) @register_test_case(module_factory=lambda: OnesModuleFloat()) def OnesModuleFloat_basic(module, tu: TestUtils): module.forward() class OnesModuleFalsePinMemory(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ]) def forward(self): return torch.ones(3, 4, dtype=torch.float32, pin_memory=False) @register_test_case(module_factory=lambda: OnesModuleFalsePinMemory()) def OnesModuleFalsePinMemory_basic(module, tu: TestUtils): module.forward() # ============================================================================== class EmptyContiguousModule(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ]) def forward(self): return torch.empty((3, 4), memory_format=torch.contiguous_format).fill_(0) @register_test_case(module_factory=lambda: EmptyContiguousModule()) def EmptyModule_contiguous(module, tu: TestUtils): module.forward() class EmptyDefaultDtypeModule(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ]) def forward(self): return torch.empty((3, 4)).fill_(0) @register_test_case(module_factory=lambda: EmptyDefaultDtypeModule()) def EmptyModule_defaultDtype(module, tu: TestUtils): module.forward() class EmptyIntModule(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ]) def forward(self): return torch.empty((3, 4), dtype=torch.int64).fill_(0) @register_test_case(module_factory=lambda: EmptyIntModule()) def EmptyModule_int(module, tu: TestUtils): module.forward() class EmptyFloatModule(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ]) def forward(self): return torch.empty((3, 4), dtype=torch.float32).fill_(0) @register_test_case(module_factory=lambda: EmptyFloatModule()) def EmptyModule_float(module, tu: TestUtils): module.forward() class EmptyFalsePinMemoryModule(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ]) def forward(self): return torch.empty((3, 4), dtype=torch.float32, pin_memory=False).fill_(0) @register_test_case(module_factory=lambda: EmptyFalsePinMemoryModule()) def EmptyModule_falsePinMemory(module, tu: TestUtils): module.forward() # ============================================================================== class EmptyLikeDefaultDtypeModule(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ([-1, -1], torch.float32, True), ]) def forward(self, a): return torch.empty_like(a).fill_(0) @register_test_case(module_factory=lambda: EmptyLikeDefaultDtypeModule()) def EmptyLikeModule_defaultDtype(module, tu: TestUtils): module.forward(tu.rand(3, 5)) class EmptyLikeIntModule(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ([-1, -1], torch.int64, True), ]) def forward(self, a): return torch.empty_like(a, dtype=torch.int32).fill_(0) @register_test_case(module_factory=lambda: EmptyLikeIntModule()) def EmptyLikeModule_int(module, tu: TestUtils): module.forward(torch.randint(10, (3, 5))) class EmptyLikeFloatModule(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ([-1, -1], torch.float32, True), ]) def forward(self, a): return torch.empty_like(a, dtype=torch.float32).fill_(0) @register_test_case(module_factory=lambda: EmptyLikeFloatModule()) def EmptyLikeModule_float(module, tu: TestUtils): module.forward(tu.rand(4, 5)) class EmptyLikeFalsePinMemoryModule(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ([-1, -1, -1], torch.float32, True), ]) def forward(self, a): return torch.empty_like(a, dtype=torch.float64, pin_memory=False).fill_(0) @register_test_case(module_factory=lambda: EmptyLikeFalsePinMemoryModule()) def EmptyLikeModule_falsePinMemory(module, tu: TestUtils): module.forward(tu.rand(2, 3, 4)) # ============================================================================== class ZerosLikeDefaultDtypeModule(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ([-1, -1], torch.float32, True), ]) def forward(self, a): return torch.zeros_like(a) @register_test_case(module_factory=lambda: ZerosLikeDefaultDtypeModule()) def ZerosLikeModule_defaultDtype(module, tu: TestUtils): module.forward(tu.rand(3, 5)) class ZerosLikeIntModule(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ([-1, -1], torch.int64, True), ]) def forward(self, a): return torch.zeros_like(a, dtype=torch.int32) @register_test_case(module_factory=lambda: ZerosLikeIntModule()) def ZerosLikeModule_int(module, tu: TestUtils): module.forward(torch.randint(10, (3, 5))) class ZerosLikeFloatModule(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ([-1, -1], torch.float32, True), ]) def forward(self, a): return torch.zeros_like(a, dtype=torch.float32) @register_test_case(module_factory=lambda: ZerosLikeFloatModule()) def ZerosLikeModule_float(module, tu: TestUtils): module.forward(tu.rand(4, 5)) class ZerosLikeFalsePinMemoryModule(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ([-1, -1, -1], torch.float32, True), ]) def forward(self, a): return torch.zeros_like(a, dtype=torch.float64, pin_memory=False) @register_test_case(module_factory=lambda: ZerosLikeFalsePinMemoryModule()) def ZerosLikeModule_falsePinMemory(module, tu: TestUtils): module.forward(tu.rand(2, 3, 4)) # ============================================================================== class OnesLikeDefaultDtypeModule(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ([-1, -1], torch.float32, True), ]) def forward(self, a): return torch.ones_like(a) @register_test_case(module_factory=lambda: OnesLikeDefaultDtypeModule()) def OnesLikeModule_defaultDtype(module, tu: TestUtils): module.forward(tu.rand(3, 5)) class OnesLikeIntModule(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ([-1, -1], torch.int64, True), ]) def forward(self, a): return torch.ones_like(a, dtype=torch.int32) @register_test_case(module_factory=lambda: OnesLikeIntModule()) def OnesLikeModule_int(module, tu: TestUtils): module.forward(torch.randint(10, (3, 5))) class OnesLikeFloatModule(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ([-1, -1], torch.float32, True), ]) def forward(self, a): return torch.ones_like(a, dtype=torch.float32) @register_test_case(module_factory=lambda: OnesLikeFloatModule()) def OnesLikeModule_float(module, tu: TestUtils): module.forward(tu.rand(4, 5)) class OnesLikeFalsePinMemoryModule(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ([-1, -1, -1], torch.float32, True), ]) def forward(self, a): return torch.ones_like(a, dtype=torch.float64, pin_memory=False) @register_test_case(module_factory=lambda: OnesLikeFalsePinMemoryModule()) def OnesLikeModule_falsePinMemory(module, tu: TestUtils): module.forward(tu.rand(2, 3, 4)) # ============================================================================== class Fill_TensorFloat64WithFloat32(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ([-1, -1, -1], torch.float32, True), ]) def forward(self, tensor): return torch.ops.aten.fill_(tensor, 3.0) @register_test_case(module_factory=lambda: Fill_TensorFloat64WithFloat32()) def Fill_TensorFloat64WithFloat32_basic(module, tu: TestUtils): module.forward(torch.randn(3, 2, 4)) class Fill_TensorFloat64WithFloat64(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ([-1, -1, -1], torch.float64, True), ]) def forward(self, tensor): return torch.ops.aten.fill_(tensor, 3.0) @register_test_case(module_factory=lambda: Fill_TensorFloat64WithFloat64()) def Fill_TensorFloat64WithFloat64_basic(module, tu: TestUtils): module.forward(torch.randn(3, 2, 4).to(torch.float64)) class Fill_TensorFloat64WithInt64(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ([-1, -1, -1], torch.float64, True), ]) def forward(self, tensor): return torch.ops.aten.fill_(tensor, 3) @register_test_case(module_factory=lambda: Fill_TensorFloat64WithInt64()) def Fill_TensorFloat64WithInt64_basic(module, tu: TestUtils): module.forward(torch.randn(3, 2, 4).to(torch.float64)) # ============================================================================== class NewZerosModuleDefaultDtype(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ([-1, -1], torch.float32, True), ]) def forward(self, a): return torch.ops.aten.new_zeros(a, [3, 4]) @register_test_case(module_factory=lambda: NewZerosModuleDefaultDtype()) def NewZerosModuleDefaultDtype_basic(module, tu: TestUtils): module.forward(tu.rand(2, 3)) class NewZerosModuleInt2D(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ([-1, -1, -1], torch.float32, True), ]) def forward(self, a): return torch.ops.aten.new_zeros(a, [3, 4], dtype=torch.int64) @register_test_case(module_factory=lambda: NewZerosModuleInt2D()) def NewZerosModuleInt2D_basic(module, tu: TestUtils): module.forward(tu.rand(2, 3, 4)) class NewZerosModuleInt3D(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ([-1, -1], torch.float32, True), ]) def forward(self, a): return torch.ops.aten.new_zeros(a, [3, 4, 5], dtype=torch.int64) @register_test_case(module_factory=lambda: NewZerosModuleInt3D()) def NewZerosModuleInt3D_basic(module, tu: TestUtils): module.forward(tu.rand(2, 3)) class NewZerosModuleFloat2D(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ([-1, -1, -1], torch.int64, True), ]) def forward(self, a): return torch.ops.aten.new_zeros(a, [3, 4], dtype=torch.float32) @register_test_case(module_factory=lambda: NewZerosModuleFloat2D()) def NewZerosModuleFloat2D_basic(module, tu: TestUtils): module.forward(torch.randint(10, (2, 3, 4))) class NewZerosModuleFloat3D(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ([-1, -1], torch.int64, True), ]) def forward(self, a): return torch.ops.aten.new_zeros(a, [3, 4, 5], dtype=torch.float32) @register_test_case(module_factory=lambda: NewZerosModuleFloat3D()) def NewZerosModuleFloat3D_basic(module, tu: TestUtils): module.forward(torch.randint(10, (2, 3))) class NewZerosModuleFalsePinMemory(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ([-1, -1], torch.int64, True), ]) def forward(self, a): return torch.ops.aten.new_zeros(a, [3, 4], dtype=torch.float32, pin_memory=False) @register_test_case(module_factory=lambda: NewZerosModuleFalsePinMemory()) def NewZerosModuleFalsePinMemory_basic(module, tu: TestUtils): module.forward(torch.randint(10, (2, 3))) # ============================================================================== class NewOnesModuleDefaultDtype(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ([-1, -1], torch.float32, True), ]) def forward(self, a): return torch.ops.aten.new_ones(a, [3, 4]) @register_test_case(module_factory=lambda: NewOnesModuleDefaultDtype()) def NewOnesModuleDefaultDtype_basic(module, tu: TestUtils): module.forward(tu.rand(2, 3)) class NewOnesModuleInt2D(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ([-1, -1, -1], torch.float32, True), ]) def forward(self, a): return torch.ops.aten.new_ones(a, [3, 4], dtype=torch.int64) @register_test_case(module_factory=lambda: NewOnesModuleInt2D()) def NewOnesModuleInt2D_basic(module, tu: TestUtils): module.forward(tu.rand(2, 3, 4)) class NewOnesModuleInt3D(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ([-1, -1], torch.float32, True), ]) def forward(self, a): return torch.ops.aten.new_ones(a, [3, 4, 5], dtype=torch.int64) @register_test_case(module_factory=lambda: NewOnesModuleInt3D()) def NewOnesModuleInt3D_basic(module, tu: TestUtils): module.forward(tu.rand(2, 3)) class NewOnesModuleFloat2D(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ([-1, -1, -1], torch.int64, True), ]) def forward(self, a): return torch.ops.aten.new_ones(a, [3, 4], dtype=torch.float32) @register_test_case(module_factory=lambda: NewOnesModuleFloat2D()) def NewOnesModuleFloat2D_basic(module, tu: TestUtils): module.forward(torch.randint(10, (2, 3, 4))) class NewOnesModuleFloat3D(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ([-1, -1], torch.int64, True), ]) def forward(self, a): return torch.ops.aten.new_ones(a, [3, 4, 5], dtype=torch.float32) @register_test_case(module_factory=lambda: NewOnesModuleFloat3D()) def NewOnesModuleFloat3D_basic(module, tu: TestUtils): module.forward(torch.randint(10, (2, 3))) class NewOnesModuleFalsePinMemory(torch.nn.Module): def __init__(self): super().__init__() @export @annotate_args([ None, ([-1, -1], torch.int64, True), ]) def forward(self, a): return torch.ops.aten.new_ones(a, [3, 4], dtype=torch.float32, pin_memory=False) @register_test_case(module_factory=lambda: NewOnesModuleFalsePinMemory()) def NewOnesModuleFalsePinMemory_basic(module, tu: TestUtils): module.forward(torch.randint(10, (2, 3)))