def incorrects() -> None:
# T1 + T2 is incorrectly typed, due to different dimensions in the tensors
# pyre-fixme[58]: `+` is not supported for operand types `Tensor[int, [int,
# int]]` and `Tensor[int, [int, int]]`.
Err1 = T1 + T2 # noqa
# T1 * T3 is incorrectly typed
# pyre-fixme[6]: Expected `Tensor[DType, B, C]` for 2nd param but got
# `Tensor[int, T, T]`.
Err2 = mm(T1, T3) # noqa
# T1 + T4 is incorrectly type (dtype)
# pyre-fixme[58]: `+` is not supported for operand types `Tensor[int, [int,
# int]]` and `Tensor[float, [int, int]]`.
Err3 = T1 + T3 # noqa
def incorrects() -> None:
# T1 + T2 is incorrectly typed
# pyre-fixme[6]: Expected `Tensor[int, typing_extensions.Literal[42],
# typing_extensions.Literal[16]]` for 1st param but got `Tensor[int,
# typing_extensions.Literal[16], typing_extensions.Literal[64]]`.
Err1 = T1 + T2 # noqa
# T1 * T3 is incorrectly typed
# pyre-fixme[6]: Expected `Tensor[DType, B, C]` for 2nd param but got
# `Tensor[int, T, T]`.
Err2 = mm(T1, T3) # noqa
# T1 + T4 is incorrectly type (dtype)
# pyre-fixme[6]: Expected `Tensor[int, typing_extensions.Literal[42],
# typing_extensions.Literal[16]]` for 1st param but got `Tensor[int, T, T]`.
Err3 = T1 + T3 # noqa
def f(x: Tensor[float32, [N, D4]]) -> Tensor[float32, [N, D1]]:
"""Approximated function."""
return torch.mm(x, W_target) + b_target.item()
# and a dummy one without a real value (could be an unknown Batch Size)
class T:
pass
T1: Tensor[int32, [D1, D2]] = Tensor()
T2: Tensor[int32, [D2, D3]] = Tensor()
T3: Tensor[int32, [T, T]] = Tensor()
T4: Tensor[float32, [D1, D2]] = Tensor()
# T1 + T1 is correctly typed
T1p1: Tensor[int32, [D1, D2]] = T1 + T1
# T1 * T2 is correctly typed
T1m2: Tensor[int32, [D1, D3]] = mm(T1, T2)
def incorrects() -> None:
# T1 + T2 is incorrectly typed
# pyre-fixme[6]: Expected `Tensor[int, typing_extensions.Literal[42],
# typing_extensions.Literal[16]]` for 1st param but got `Tensor[int,
# typing_extensions.Literal[16], typing_extensions.Literal[64]]`.
Err1 = T1 + T2 # noqa
# T1 * T3 is incorrectly typed
# pyre-fixme[6]: Expected `Tensor[DType, B, C]` for 2nd param but got
# `Tensor[int, T, T]`.
Err2 = mm(T1, T3) # noqa
# T1 + T4 is incorrectly type (dtype)
# pyre-fixme[6]: Expected `Tensor[int, typing_extensions.Literal[42],
# typing_extensions.Literal[16]]` for 1st param but got `Tensor[int, T, T]`.
# and a dummy one without a real value (could be an unknown Batch Size)
class T:
pass
T1: Tensor[int32, D1, D2] = Tensor()
T2: Tensor[int32, D2, D3] = Tensor()
T3: Tensor[int32, T, T] = Tensor()
T4: Tensor[float32, D1, D2] = Tensor()
T5: Tensor[str, D1, D1] = Tensor()
# T1 + T1 is correctly typed
T1p1: Tensor[int32, D1, D2] = T1 + T1
# T1 * T2 is correctly typed
T1m2: Tensor[int32, D1, D3] = mm(T1, T2)
def incorrects() -> None:
# T1 + T2 is incorrectly typed
# pyre-fixme[6]: Expected `Tensor[int, typing_extensions.Literal[42],
# typing_extensions.Literal[16]]` for 1st param but got `Tensor[int,
# typing_extensions.Literal[16], typing_extensions.Literal[64]]`.
Err1 = T1 + T2 # noqa
# T1 * T3 is incorrectly typed
# pyre-fixme[6]: Expected `Tensor[DType, B, C]` for 2nd param but got
# `Tensor[int, T, T]`.
Err2 = mm(T1, T3) # noqa
# T1 + T4 is incorrectly type (dtype)
# pyre-fixme[6]: Expected `Tensor[int, typing_extensions.Literal[42],
# typing_extensions.Literal[16]]` for 1st param but got `Tensor[int, T, T]`.