[tests] remove TF tests (uses of require_tf) (#38944)

* remove uses of require_tf

* remove redundant import guards

* this class has no tests

* nits

* del tf rng comment
This commit is contained in:
Joao Gante
2025-06-25 18:29:10 +01:00
committed by GitHub
parent d37f751797
commit 1d45d90e5d
44 changed files with 21 additions and 2504 deletions

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@@ -473,13 +473,6 @@ Hier ist zum Beispiel ein Test, der nur ausgeführt werden muss, wenn 2 oder meh
def test_example_with_multi_gpu():
```
Wenn ein Test `tensorflow` benötigt, verwenden Sie den Dekorator `require_tf`. Zum Beispiel:
```python no-style
@require_tf
def test_tf_thing_with_tensorflow():
```
Diese Dekors können gestapelt werden. Wenn zum Beispiel ein Test langsam ist und mindestens eine GPU unter pytorch benötigt, können Sie
wie Sie ihn einrichten können:
@@ -1204,9 +1197,6 @@ if torch.cuda.is_available():
import numpy as np
np.random.seed(seed)
# tf RNG
tf.random.set_seed(seed)
```
### Tests debuggen

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@@ -474,13 +474,6 @@ For example, here is a test that must be run only when there are 2 or more GPUs
def test_example_with_multi_gpu():
```
If a test requires `tensorflow` use the `require_tf` decorator. For example:
```python no-style
@require_tf
def test_tf_thing_with_tensorflow():
```
These decorators can be stacked. For example, if a test is slow and requires at least one GPU under pytorch, here is
how to set it up:
@@ -1226,11 +1219,6 @@ if torch.cuda.is_available():
import numpy as np
np.random.seed(seed)
# tf RNG
import tensorflow as tf
tf.random.set_seed(seed)
```
### Debugging tests

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@@ -445,13 +445,6 @@ CUDA_VISIBLE_DEVICES="1" pytest tests/utils/test_logging.py
def test_example_with_multi_gpu():
```
テストに `tensorflow` が必要な場合は、`require_tf` デコレータを使用します。例えば:
```python no-style
@require_tf
def test_tf_thing_with_tensorflow():
```
これらのデコレータは積み重ねることができます。たとえば、テストが遅く、pytorch で少なくとも 1 つの GPU が必要な場合は、次のようになります。
設定方法:
@@ -1135,9 +1128,6 @@ if torch.cuda.is_available():
import numpy as np
np.random.seed(seed)
# tf RNG
tf.random.set_seed(seed)
```

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@@ -473,13 +473,6 @@ GPU 요구 사항을 표로 정리하면 아래와 같습니디ㅏ:
def test_example_with_multi_gpu():
```
`tensorflow`가 필요한 경우 `require_tf` 데코레이터를 사용합니다. 예를 들어 다음과 같습니다:
```python no-style
@require_tf
def test_tf_thing_with_tensorflow():
```
이러한 데코레이터는 중첩될 수 있습니다.
예를 들어, 느린 테스트로 진행되고 pytorch에서 적어도 하나의 GPU가 필요한 경우 다음과 같이 설정할 수 있습니다: