# tensorplay.testing API

Source: https://www.tensorplay.cn/docs/api/tensorplay.testing.html

## Functions 5

[#](#api-tensorplay.testing.assert_allclose)

### assert_allclose

function[Full reference ↗](/docs/generated/tensorplay.testing.assert_allclose.html)

```python
tensorplay.testing.assert_allclose(actual: Any, expected: Any, rtol: float | None = None, atol: float | None = None, equal_nan: bool = True, msg: str = '') → None
```

Legacy alias of [assert_close()](/docs/generated/tensorplay.testing.assert_close.html#tensorplay.testing.assert_close) with positional tolerances.

[#](#api-tensorplay.testing.assert_close)

### assert_close

function[Full reference ↗](/docs/generated/tensorplay.testing.assert_close.html)

```python
tensorplay.testing.assert_close(actual: Any, expected: Any, *, allow_subclasses: bool = True, rtol: float | None = None, atol: float | None = None, equal_nan: bool = False, check_device: bool = True, check_dtype: bool = True, check_layout: bool = True, check_stride: bool = False, msg: str | Callable[[str], str] | None = None)
```

Asserts that actual and expected are close.

If actual and expected are strided and finite, they are considered
close if

$$\lvert \text{actual} - \text{expected} \rvert \le \texttt{atol} + \texttt{rtol} \cdot \lvert \text{expected} \rvert$$

Non-finite values (-inf and inf) are only considered close if and
only if they are equal. NaN’s are only considered equal to each other
if equal_nan is True.

In addition, they are only considered close if they have the same

- device (if check_device is True),

- dtype (if check_dtype is True),

- layout (if check_layout is True), and

- stride (if check_stride is True).

If either actual or expected is a scalar or a nested python
container, the other side is converted to a tensor-like value before the
comparison.

Parameters:

- actual (Any) – Actual input.

- expected (Any) – Expected input.

- allow_subclasses ([bool](https://docs.python.org/3/builtins/functions.html#bool)) – If True (default) and other than exact type match, inputs that are subclasses of each other are considered close.

- rtol (Optional[[float](https://docs.python.org/3/builtins/functions.html#float)]) – Relative tolerance. If specified atol must also be specified. If omitted, default values based on the dtype are selected. See below for details.

- atol (Optional[[float](https://docs.python.org/3/builtins/functions.html#float)]) – Absolute tolerance. If specified rtol must also be specified. If omitted, default values based on the dtype are selected. See below for details.

- equal_nan ([bool](https://docs.python.org/3/builtins/functions.html#bool)) – If True, two NaN values are considered equal. Defaults to False.

- check_device ([bool](https://docs.python.org/3/builtins/functions.html#bool)) – If True (default), asserts that corresponding tensors are on the same device.

- check_dtype ([bool](https://docs.python.org/3/builtins/functions.html#bool)) – If True (default), asserts that corresponding tensors have the same dtype.

- check_layout ([bool](https://docs.python.org/3/builtins/functions.html#bool)) – If True (default), asserts that corresponding tensors have the same layout.

- check_stride ([bool](https://docs.python.org/3/builtins/functions.html#bool)) – If True, asserts that corresponding strided tensors have the same stride.

- msg (Optional[Union[[str](https://docs.python.org/3/builtins/stdtypes.html#str), Callable[[[str](https://docs.python.org/3/builtins/stdtypes.html#str)], [str](https://docs.python.org/3/builtins/stdtypes.html#str)]]]) – Optional error message to use in case of failure.

Raises:

- [ValueError](https://docs.python.org/3/builtins/exceptions.html#ValueError) – If only rtol or only atol is specified.

- [AssertionError](https://docs.python.org/3/builtins/exceptions.html#AssertionError) – If corresponding values are not close.

Default tolerances by dtype:

| dtype |rtol |atol |
| --- | --- | --- |
| float16 | 1e-3 | 1e-5 |
| bfloat16 | 1.6e-2 | 1e-5 |
| float32 | 1.3e-6 | 1e-5 |
| float64 | 1e-7 | 1e-7 |
| complex64 | 1.3e-6 | 1e-5 |
| complex128 | 1e-7 | 1e-7 |

> **Note**
>
> Tensors are compared elementwise, allowing for a relative and an absolute tolerance per element. If both tolerances are omitted, the loosest tolerance of the involved dtypes is selected.

[#](#api-tensorplay.testing.default_tolerances)

### default_tolerances

function[Full reference ↗](/docs/generated/tensorplay.testing.default_tolerances.html)

```python
tensorplay.testing.default_tolerances(*inputs: Tensor | dtype, dtype_precisions: dict[dtype, tuple[float, float]] | None = None) → tuple[float, float]
```

Returns the default absolute and relative testing tolerances for a set of inputs based on the dtype.

Returns:

Loosest tolerances of all input dtypes.

Return type:

(Tuple[[float](https://docs.python.org/3/builtins/functions.html#float), [float](https://docs.python.org/3/builtins/functions.html#float)])

[#](#api-tensorplay.testing.get_tolerances)

### get_tolerances

function[Full reference ↗](/docs/generated/tensorplay.testing.get_tolerances.html)

```python
tensorplay.testing.get_tolerances(*inputs: Tensor | dtype, rtol: float | None, atol: float | None, id: tuple[Any, ...] = ()) → tuple[float, float]
```

Gets absolute and relative tolerances to be used for numeric comparisons.

If both rtol and atol are specified, this is a no-op. If neither is
specified, [default_tolerances()](/docs/generated/tensorplay.testing.default_tolerances.html#tensorplay.testing.default_tolerances) is used. Specifying only one raises a
[ValueError](https://docs.python.org/3/builtins/exceptions.html#ValueError), since a single tolerance might lead to surprising
results.

[#](#api-tensorplay.testing.make_tensor)

### make_tensor

function[Full reference ↗](/docs/generated/tensorplay.testing.make_tensor.html)

```python
tensorplay.testing.make_tensor(*shape: int | Size | list[int] | tuple[int, ...], dtype: dtype, device: str | device, low: float | None = None, high: float | None = None, requires_grad: bool = False, noncontiguous: bool = False, exclude_zero: bool = False) → Tensor
```

Creates a tensor with the given shape, device, and
dtype, filled with values drawn uniformly from [low, high).

If low or high are outside the range of the
dtype’s representable finite values, they are clamped to the
lowest or highest representable finite value, respectively. If None,
they default to -9 and 9 respectively (0 and 2 for
bool).

Parameters:

- shape (Tuple[[int](https://docs.python.org/3/builtins/functions.html#int), ...]) – Single integer or a collection of integers defining the shape of the output tensor.

- dtype ([tensorplay.dtype](/docs/generated/tensorplay.DType.html#tensorplay.DType)) – The data type of the returned tensor.

- device (Union[[str](https://docs.python.org/3/builtins/stdtypes.html#str), [tensorplay.device](/docs/generated/tensorplay.Device.html#tensorplay.Device)]) – The device of the returned tensor.

- low (Optional[Number]) – Sets the lower limit of the range of the values in the returned tensor.

- high (Optional[Number]) – Sets the upper limit of the range of the values in the returned tensor.

- requires_grad ([bool](https://docs.python.org/3/builtins/functions.html#bool)) – If True, the returned tensor is set to require gradient.

- noncontiguous ([bool](https://docs.python.org/3/builtins/functions.html#bool)) – If True, the returned tensor is non-contiguous.

- exclude_zero ([bool](https://docs.python.org/3/builtins/functions.html#bool)) – If True, zeros in the returned tensor are replaced by the smallest normal value of the dtype (1 for boolean and integral dtypes).

Raises:

- [ValueError](https://docs.python.org/3/builtins/exceptions.html#ValueError) – If low >= high, or if the interval [low, high) does not intersect the dtype’s representable range.

- [TypeError](https://docs.python.org/3/builtins/exceptions.html#TypeError) – For unsupported dtypes.

## Classes 1

[#](#api-tensorplay.testing.FileCheck)

### FileCheck

class[Full reference ↗](/docs/generated/tensorplay.testing.FileCheck.html)

```python
class tensorplay.testing.FileCheck
```

```python
check(self: tensorplay._C.FileCheck, test_string: str) → tensorplay._C.FileCheck
```

```python
check_count(self: tensorplay._C.FileCheck, test_string: str, count: SupportsInt | SupportsIndex, exactly: bool = False) → tensorplay._C.FileCheck
```

```python
check_dag(self: tensorplay._C.FileCheck, test_string: str) → tensorplay._C.FileCheck
```

```python
check_next(self: tensorplay._C.FileCheck, test_string: str) → tensorplay._C.FileCheck
```

```python
check_not(self: tensorplay._C.FileCheck, test_string: str) → tensorplay._C.FileCheck
```

```python
check_regex(self: tensorplay._C.FileCheck, test_string: str) → tensorplay._C.FileCheck
```

```python
check_same(self: tensorplay._C.FileCheck, test_string: str) → tensorplay._C.FileCheck
```

```python
check_source_highlighted(self: tensorplay._C.FileCheck, test_string: str) → tensorplay._C.FileCheck
```

```python
run(self: tensorplay._C.FileCheck, test_string: str) → None
```