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Merged
patrickvonplaten merged 1 commit into from
Nov 9, 2022
Merged

Flax tests: don't hardcode number of devices #1175

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47 changes: 26 additions & 21 deletions tests/test_pipelines_flax.py
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Original file line number Diff line number Diff line change
Expand Up @@ -73,18 +73,19 @@ def test_dummy_all_tpus(self):

# shard inputs and rng
params = replicate(params)
prng_seed = jax.random.split(prng_seed, 8)
prng_seed = jax.random.split(prng_seed, num_samples)
prompt_ids = shard(prompt_ids)

images = p_sample(prompt_ids, params, prng_seed, num_inference_steps).images

assert images.shape == (8, 1, 128, 128, 3)
assert np.abs(np.abs(images[0, 0, :2, :2, -2:], dtype=np.float32).sum() - 3.1111548) < 1e-3
assert np.abs(np.abs(images, dtype=np.float32).sum() - 199746.95) < 5e-1
assert images.shape == (num_samples, 1, 128, 128, 3)
if jax.device_count() == 8:
assert np.abs(np.abs(images[0, 0, :2, :2, -2:], dtype=np.float32).sum() - 3.1111548) < 1e-3
assert np.abs(np.abs(images, dtype=np.float32).sum() - 199746.95) < 5e-1

images_pil = pipeline.numpy_to_pil(np.asarray(images.reshape((num_samples,) + images.shape[-3:])))

assert len(images_pil) == 8
assert len(images_pil) == num_samples

def test_stable_diffusion_v1_4(self):
pipeline, params = FlaxStableDiffusionPipeline.from_pretrained(
Expand All @@ -107,14 +108,15 @@ def test_stable_diffusion_v1_4(self):

# shard inputs and rng
params = replicate(params)
prng_seed = jax.random.split(prng_seed, 8)
prng_seed = jax.random.split(prng_seed, num_samples)
prompt_ids = shard(prompt_ids)

images = p_sample(prompt_ids, params, prng_seed, num_inference_steps).images

assert images.shape == (8, 1, 512, 512, 3)
assert np.abs((np.abs(images[0, 0, :2, :2, -2:], dtype=np.float32).sum() - 0.05652401)) < 1e-3
assert np.abs((np.abs(images, dtype=np.float32).sum() - 2383808.2)) < 5e-1
assert images.shape == (num_samples, 1, 512, 512, 3)
if jax.device_count() == 8:
assert np.abs((np.abs(images[0, 0, :2, :2, -2:], dtype=np.float32).sum() - 0.05652401)) < 1e-3
assert np.abs((np.abs(images, dtype=np.float32).sum() - 2383808.2)) < 5e-1

def test_stable_diffusion_v1_4_bfloat_16(self):
pipeline, params = FlaxStableDiffusionPipeline.from_pretrained(
Expand All @@ -137,14 +139,15 @@ def test_stable_diffusion_v1_4_bfloat_16(self):

# shard inputs and rng
params = replicate(params)
prng_seed = jax.random.split(prng_seed, 8)
prng_seed = jax.random.split(prng_seed, num_samples)
prompt_ids = shard(prompt_ids)

images = p_sample(prompt_ids, params, prng_seed, num_inference_steps).images

assert images.shape == (8, 1, 512, 512, 3)
assert np.abs((np.abs(images[0, 0, :2, :2, -2:], dtype=np.float32).sum() - 0.06652832)) < 1e-3
assert np.abs((np.abs(images, dtype=np.float32).sum() - 2384849.8)) < 5e-1
assert images.shape == (num_samples, 1, 512, 512, 3)
if jax.device_count() == 8:
assert np.abs((np.abs(images[0, 0, :2, :2, -2:], dtype=np.float32).sum() - 0.06652832)) < 1e-3
assert np.abs((np.abs(images, dtype=np.float32).sum() - 2384849.8)) < 5e-1

def test_stable_diffusion_v1_4_bfloat_16_with_safety(self):
pipeline, params = FlaxStableDiffusionPipeline.from_pretrained(
Expand All @@ -165,14 +168,15 @@ def test_stable_diffusion_v1_4_bfloat_16_with_safety(self):

# shard inputs and rng
params = replicate(params)
prng_seed = jax.random.split(prng_seed, 8)
prng_seed = jax.random.split(prng_seed, num_samples)
prompt_ids = shard(prompt_ids)

images = pipeline(prompt_ids, params, prng_seed, num_inference_steps, jit=True).images

assert images.shape == (8, 1, 512, 512, 3)
assert np.abs((np.abs(images[0, 0, :2, :2, -2:], dtype=np.float32).sum() - 0.06652832)) < 1e-3
assert np.abs((np.abs(images, dtype=np.float32).sum() - 2384849.8)) < 5e-1
assert images.shape == (num_samples, 1, 512, 512, 3)
if jax.device_count() == 8:
assert np.abs((np.abs(images[0, 0, :2, :2, -2:], dtype=np.float32).sum() - 0.06652832)) < 1e-3
assert np.abs((np.abs(images, dtype=np.float32).sum() - 2384849.8)) < 5e-1

def test_stable_diffusion_v1_4_bfloat_16_ddim(self):
scheduler = FlaxDDIMScheduler(
Expand Down Expand Up @@ -210,11 +214,12 @@ def test_stable_diffusion_v1_4_bfloat_16_ddim(self):

# shard inputs and rng
params = replicate(params)
prng_seed = jax.random.split(prng_seed, 8)
prng_seed = jax.random.split(prng_seed, num_samples)
prompt_ids = shard(prompt_ids)

images = p_sample(prompt_ids, params, prng_seed, num_inference_steps).images

assert images.shape == (8, 1, 512, 512, 3)
assert np.abs((np.abs(images[0, 0, :2, :2, -2:], dtype=np.float32).sum() - 0.045043945)) < 1e-3
assert np.abs((np.abs(images, dtype=np.float32).sum() - 2347693.5)) < 5e-1
assert images.shape == (num_samples, 1, 512, 512, 3)
if jax.device_count() == 8:
assert np.abs((np.abs(images[0, 0, :2, :2, -2:], dtype=np.float32).sum() - 0.045043945)) < 1e-3
assert np.abs((np.abs(images, dtype=np.float32).sum() - 2347693.5)) < 5e-1