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import importlib.util
import io
import sys
import types
from pathlib import Path
import torch
from PIL import Image
_SPEC = importlib.util.spec_from_file_location(
"easy_media_sampling_preview_test",
Path(__file__).parents[1] / "utils" / "sampling_preview.py",
)
assert _SPEC is not None and _SPEC.loader is not None
sampling_preview = importlib.util.module_from_spec(_SPEC)
_SPEC.loader.exec_module(sampling_preview)
def _install_preview_transport(monkeypatch, *, prompt_id="prompt-1", client_id="client"):
server = types.SimpleNamespace(
client_id=client_id,
last_node_id="project-42",
)
server_module = types.ModuleType("server")
server_module.PromptServer = types.SimpleNamespace(instance=server)
execution_utils = types.ModuleType("comfy_execution.utils")
execution_utils.get_executing_context = lambda: types.SimpleNamespace(
prompt_id=prompt_id
)
execution_package = types.ModuleType("comfy_execution")
execution_package.utils = execution_utils
monkeypatch.setitem(sys.modules, "server", server_module)
monkeypatch.setitem(sys.modules, "comfy_execution", execution_package)
monkeypatch.setitem(sys.modules, "comfy_execution.utils", execution_utils)
def test_preview_frame_count_uses_half_with_one_frame_minimum():
assert sampling_preview.preview_frame_count(121) == 60
assert sampling_preview.preview_frame_count(1) == 1
def test_preview_playback_fps_preserves_source_duration():
assert sampling_preview.preview_playback_fps(120, 24) == 12
assert sampling_preview.preview_playback_fps(121, 24) == 24 * 60 / 121
def test_async_preview_encoder_replaces_oldest_pending_work_when_full():
encoder = sampling_preview._AsyncPreviewEncoder.__new__(
sampling_preview._AsyncPreviewEncoder
)
encoder._queue = sampling_preview.queue.Queue(maxsize=2)
callback = lambda: None
encoder._queue.put_nowait((callback, ("oldest",), {}))
encoder._queue.put_nowait((callback, ("newer",), {}))
assert encoder.submit(callback, "latest") is True
queued = [encoder._queue.get_nowait()[1][0] for _ in range(2)]
assert queued == ["newer", "latest"]
def test_decode_preview_frames_accepts_channel_first_tiny_vae_output():
class PreviewVae:
def decode_video(self, latent, frame_indices=None):
assert frame_indices == [0, 2, 4]
return torch.stack([
torch.full((3, 2, 6), value / 2)
for value in range(3)
])
frames = sampling_preview.decode_preview_frames(
PreviewVae(), torch.zeros((1, 24, 5, 2, 6)), 3
)
assert len(frames) == 3
assert frames[1].size == (6, 2)
assert frames[1].getpixel((0, 0)) == (128, 128, 128)
def test_decode_preview_frames_resamples_sparse_latents_to_requested_count():
class PreviewVae:
def decode_video(self, latent, frame_indices=None):
return torch.zeros((len(frame_indices), 3, 2, 2))
frames = sampling_preview.decode_preview_frames(
PreviewVae(), torch.zeros((1, 24, 3, 2, 2)), 6
)
assert len(frames) == 6
def test_decode_preview_frames_interpolates_sparse_frames_continuously():
class PreviewVae:
def decode_video(self, latent, frame_indices=None):
return torch.stack([
torch.zeros((3, 2, 2)),
torch.ones((3, 2, 2)),
])
frames = sampling_preview.decode_preview_frames(
PreviewVae(), torch.zeros((1, 24, 2, 2, 2)), 3
)
assert [frame.getpixel((0, 0))[0] for frame in frames] == [0, 128, 255]
def test_decode_preview_frames_preserves_uint8_tiny_vae_pixels():
class PreviewVae:
def decode_video(self, latent, frame_indices=None):
return torch.full((len(frame_indices), 3, 2, 2), 64, dtype=torch.uint8)
frames = sampling_preview.decode_preview_frames(
PreviewVae(), torch.zeros((1, 24, 2, 2, 2)), 2
)
assert frames[0].getpixel((0, 0)) == (64, 64, 64)
def test_decode_preview_frames_resamples_uint8_without_clipping_to_white():
class PreviewVae:
def decode_video(self, latent, frame_indices=None):
return torch.stack([
torch.zeros((3, 2, 2), dtype=torch.uint8),
torch.full((3, 2, 2), 128, dtype=torch.uint8),
])
frames = sampling_preview.decode_preview_frames(
PreviewVae(), torch.zeros((1, 24, 2, 2, 2)), 3
)
assert [frame.getpixel((0, 0))[0] for frame in frames] == [0, 64, 128]
def test_decode_preview_frames_accepts_batched_channel_first_video_output():
class PreviewVae:
def decode_video(self, latent, frame_indices=None):
values = torch.tensor([0.0, 0.25, 0.5, 0.75, 1.0]).view(1, 1, 5, 1, 1)
return values.expand(1, 3, 5, 2, 6)
frames = sampling_preview.decode_preview_frames(
PreviewVae(), torch.zeros((1, 24, 5, 2, 6)), 3
)
assert len(frames) == 3
assert frames[1].size == (6, 2)
assert frames[1].getpixel((0, 0)) == (128, 128, 128)
def test_decode_preview_frames_prefers_channel_last_when_frame_count_is_rgb_sized():
class PreviewVae:
def decode_video(self, latent, frame_indices=None):
values = torch.tensor([0.0, 0.5, 1.0]).view(1, 3, 1, 1, 1)
return values.expand(1, 3, 2, 6, 3)
frames = sampling_preview.decode_preview_frames(
PreviewVae(), torch.zeros((1, 24, 3, 2, 6)), 3
)
assert len(frames) == 3
assert [frame.size for frame in frames] == [(6, 2)] * 3
assert [frame.getpixel((0, 0))[0] for frame in frames] == [0, 128, 255]
def test_encode_preview_caps_resolution_and_uses_quality_80(monkeypatch):
qualities = []
original_save = Image.Image.save
def recording_save(image, fp, format=None, **params):
qualities.append(params.get("quality"))
return original_save(image, fp, format=format, **params)
monkeypatch.setattr(Image.Image, "save", recording_save)
encoded = sampling_preview.encode_preview(
[Image.new("RGB", (1280, 720)), Image.new("RGB", (1280, 720))],
24,
)
assert encoded is not None and encoded[0] == "image/webp"
result = Image.open(io.BytesIO(encoded[1]))
assert result.size == (640, 360)
assert qualities == [80]
def test_payload_keeps_every_frame_independently_addressable(
monkeypatch,
):
sent = []
server = types.SimpleNamespace(
client_id="client",
send_sync=lambda _event, payload, _client_id=None: sent.append(payload),
)
server_module = types.ModuleType("server")
server_module.PromptServer = types.SimpleNamespace(instance=server)
monkeypatch.setitem(sys.modules, "server", server_module)
frames = [Image.new("RGB", (16, 16)) for _ in range(4)]
sampling_preview.send_preview(
frames,
node_id="42",
fps=12,
step=0,
total=8,
segment_index=0,
sampling_pass="first",
client_id="client",
prompt_id="prompt-1",
)
encoded = [
Image.open(io.BytesIO(base64.b64decode(image)))
for image in sent[0]["images"]
]
assert len(encoded) == 4
assert all(image.format == "JPEG" for image in encoded)
assert sent[0]["frame_count"] == 4
def test_send_preview_includes_playback_metadata(monkeypatch):
sent = []
server = types.SimpleNamespace(
client_id="client",
send_sync=lambda event, payload, client_id=None: sent.append(
(event, payload, client_id)
),
)
server_module = types.ModuleType("server")
server_module.PromptServer = types.SimpleNamespace(instance=server)
monkeypatch.setitem(sys.modules, "server", server_module)
sampling_preview.send_preview(
[Image.new("RGB", (2, 2)), Image.new("RGB", (2, 2))],
node_id="42",
fps=12,
step=2,
total=8,
segment_index=1,
sampling_pass="second",
client_id="client",
prompt_id="prompt-1",
display_node_id="project-42",
)
event, payload, client_id = sent[0]
assert event == sampling_preview.SAMPLING_PREVIEW_EVENT
assert client_id == "client"
assert payload["node_id"] == "42"
assert payload["display_node_id"] == "project-42"
assert payload["prompt_id"] == "prompt-1"
assert payload["step"] == 3
assert payload["frame_count"] == 2
assert payload["fps"] == 12.0
assert payload["segment_index"] == 1
assert payload["sampling_pass"] == "second"
assert base64.b64decode(payload["image"])
assert payload["mime"] == "image/jpeg"
assert len(payload["images"]) == 2
def test_send_preview_does_not_broadcast_without_a_client(monkeypatch):
sent = []
server_module = types.ModuleType("server")
server_module.PromptServer = types.SimpleNamespace(
instance=types.SimpleNamespace(send_sync=lambda *args: sent.append(args))
)
monkeypatch.setitem(sys.modules, "server", server_module)
sampling_preview.send_preview(
[Image.new("RGB", (2, 2))],
node_id="42",
fps=12,
step=0,
total=8,
segment_index=0,
sampling_pass="first",
client_id=None,
prompt_id="prompt-1",
)
assert sent == []
def test_preview_callback_submits_encoding_without_waiting(monkeypatch):
_install_preview_transport(monkeypatch)
submitted = []
monkeypatch.setattr(
sampling_preview._PREVIEW_ENCODER,
"submit",
lambda callback, *args, **kwargs: submitted.append((callback, args, kwargs)),
)
class Model:
class Inner:
@staticmethod
def process_latent_out(latent):
return latent
model = Inner()
class PreviewVae:
@staticmethod
def decode(latent):
return torch.zeros((1, 2, 2, 3))
callback = sampling_preview.create_preview_callback(
Model(),
PreviewVae(),
node_id="42",
requested_frames=1,
fps=12,
segment_index=0,
sampling_pass="first",
)
callback(0, torch.zeros((1, 4, 2, 2)), None, 8)
assert len(submitted) == 1
assert submitted[0][0] is sampling_preview.send_preview
assert submitted[0][2]["client_id"] == "client"
assert submitted[0][2]["prompt_id"] == "prompt-1"
assert submitted[0][2]["display_node_id"] == "project-42"
def test_preview_callback_unpacks_packed_h3_latent_before_decoding(monkeypatch):
_install_preview_transport(monkeypatch)
submitted = []
video = torch.zeros((1, 24, 3, 2, 6))
audio = torch.zeros((1, 8, 4, 2))
packed = torch.zeros((1, 1, video.numel() + audio.numel()))
comfy = types.ModuleType("comfy")
comfy_utils = types.ModuleType("comfy.utils")
comfy_utils.unpack_latents = lambda latent, shapes: (
[video, audio]
if latent is packed and shapes == [tuple(video.shape), tuple(audio.shape)]
else []
)
comfy.utils = comfy_utils
monkeypatch.setitem(sys.modules, "comfy", comfy)
monkeypatch.setitem(sys.modules, "comfy.utils", comfy_utils)
monkeypatch.setattr(
sampling_preview._PREVIEW_ENCODER,
"submit",
lambda callback, *args, **kwargs: submitted.append((callback, args, kwargs)),
)
class Model:
class Inner:
latent_shapes = [tuple(video.shape), tuple(audio.shape)]
@staticmethod
def process_latent_out(latent):
assert latent is video
return latent
model = Inner()
class PreviewVae:
@staticmethod
def decode_video(latent, frame_indices=None):
assert latent is video
return torch.zeros((3, 2, 6, 3))
callback = sampling_preview.create_preview_callback(
Model(),
PreviewVae(),
node_id="42",
requested_frames=3,
fps=12,
segment_index=0,
sampling_pass="first",
)
callback(0, packed, None, 8)
assert len(submitted) == 1
def test_preview_callback_isolates_optional_preview_errors(monkeypatch):
_install_preview_transport(monkeypatch)
monkeypatch.setattr(
sampling_preview,
"decode_preview_frames",
lambda *_args, **_kwargs: (_ for _ in ()).throw(OSError("encode failed")),
)
class Model:
class Inner:
@staticmethod
def process_latent_out(latent):
return latent
model = Inner()
callback = sampling_preview.create_preview_callback(
Model(),
object(),
node_id="42",
requested_frames=1,
fps=12,
segment_index=0,
sampling_pass="first",
)
callback(0, torch.zeros((1, 4, 2, 2)), None, 8)
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