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fix

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This commit is contained in:
ydshieh 2025-07-02 12:05:30 +02:00
parent e23c242848
commit fce61367b5
1 changed files with 91 additions and 40 deletions
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131
tests/models/maskformer/test_modeling_maskformer.py
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@ -21,6 +21,7 @@ import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import DetrConfig, MaskFormerConfig, SwinConfig, is_torch_available, is_vision_available
from transformers.testing_utils import (
Expectations,
require_timm,
require_torch,
require_torch_accelerator,
@ -526,13 +527,21 @@ class MaskFormerModelIntegrationTest(unittest.TestCase):
rtol=TOLERANCE,
)
expected_slice_hidden_state = torch.tensor(
[
[-0.8422, -0.8435, -0.9717],
[-1.0145, -0.5564, -0.4195],
[-1.0040, -0.4486, -0.1962],
]
).to(torch_device)
expectations = Expectations(
{
(None, None): [
[-0.8422, -0.8434, -0.9718],
[-1.0144, -0.5565, -0.4195],
[-1.0038, -0.4484, -0.1961]
],
("cuda", 8): [
[-0.8422, -0.8435, -0.9717],
[-1.0145, -0.5564, -0.4195],
[-1.0040, -0.4486, -0.1962],
],
}
)
expected_slice_hidden_state = torch.tensor(expectations.get_expectation()).to(torch_device)
torch.allclose(
outputs.pixel_decoder_last_hidden_state[0, 0, :3, :3],
expected_slice_hidden_state,
@ -540,13 +549,21 @@ class MaskFormerModelIntegrationTest(unittest.TestCase):
rtol=TOLERANCE,
)
expected_slice_hidden_state = torch.tensor(
[
[0.2853, -0.0162, 0.9736],
[0.6256, 0.1856, 0.8530],
[-0.0679, -0.4118, 1.8416],
]
).to(torch_device)
expectations = Expectations(
{
(None, None): [
[0.2852, -0.0159, 0.9735],
[0.6254, 0.1858, 0.8529],
[-0.0680, -0.4116, 1.8413],
],
("cuda", 8): [
[0.2853, -0.0162, 0.9736],
[0.6256, 0.1856, 0.8530],
[-0.0679, -0.4118, 1.8416],
],
}
)
expected_slice_hidden_state = torch.tensor(expectations.get_expectation()).to(torch_device)
torch.allclose(
outputs.transformer_decoder_last_hidden_state[0, :3, :3],
expected_slice_hidden_state,
@ -577,25 +594,42 @@ class MaskFormerModelIntegrationTest(unittest.TestCase):
masks_queries_logits.shape,
(1, model.config.decoder_config.num_queries, inputs_shape[-2] // 4, inputs_shape[-1] // 4),
)
expected_slice = [
[-1.3737, -1.7727, -1.9367],
[-1.5979, -1.9871, -2.1527],
[-1.5797, -1.9271, -2.0941],
]
expected_slice = torch.tensor(expected_slice).to(torch_device)
expectations = Expectations(
{
(None, None): [
[-1.3737124, -1.7724937, -1.9364233],
[-1.5977281, -1.9867939, -2.1523695],
[-1.5795398, -1.9269832, -2.093942],
],
("cuda", 8): [
[-1.3737, -1.7727, -1.9367],
[-1.5979, -1.9871, -2.1527],
[-1.5797, -1.9271, -2.0941],
],
}
)
expected_slice = torch.tensor(expectations.get_expectation()).to(torch_device)
torch.testing.assert_close(masks_queries_logits[0, 0, :3, :3], expected_slice, rtol=TOLERANCE, atol=TOLERANCE)
# class_queries_logits
class_queries_logits = outputs.class_queries_logits
self.assertEqual(
class_queries_logits.shape, (1, model.config.decoder_config.num_queries, model.config.num_labels + 1)
)
expected_slice = torch.tensor(
[
[1.6507e00, -5.2568e00, -3.3520e00],
[3.5767e-02, -5.9023e00, -2.9313e00],
[-6.2712e-04, -7.7627e00, -5.1268e00],
]
).to(torch_device)
expectations = Expectations(
{
(None, None): [
[1.6512e00, -5.2572e00, -3.3519e00],
[3.6169e-02, -5.9025e00, -2.9313e00],
[1.0766e-04, -7.7630e00, -5.1263e00],
],
("cuda", 8): [
[1.6507e00, -5.2568e00, -3.3520e00],
[3.5767e-02, -5.9023e00, -2.9313e00],
[-6.2712e-04, -7.7627e00, -5.1268e00],
],
}
)
expected_slice = torch.tensor(expectations.get_expectation()).to(torch_device)
torch.testing.assert_close(
outputs.class_queries_logits[0, :3, :3], expected_slice, rtol=TOLERANCE, atol=TOLERANCE
)
@ -623,25 +657,42 @@ class MaskFormerModelIntegrationTest(unittest.TestCase):
masks_queries_logits.shape,
(1, model.config.decoder_config.num_queries, inputs_shape[-2] // 4, inputs_shape[-1] // 4),
)
expected_slice = [
[-0.9000, -2.6283, -4.5964],
[-3.4123, -5.7789, -8.7919],
[-4.9132, -7.6444, -10.7557],
]
expected_slice = torch.tensor(expected_slice).to(torch_device)
expectations = Expectations(
{
(None, None): [
[-0.9046, -2.6366, -4.6062],
[-3.4179, -5.7890, -8.8057],
[-4.9179, -7.6560, -10.7711]
],
("cuda", 8): [
[-0.9000, -2.6283, -4.5964],
[-3.4123, -5.7789, -8.7919],
[-4.9132, -7.6444, -10.7557],
],
}
)
expected_slice = torch.tensor(expectations.get_expectation()).to(torch_device)
torch.testing.assert_close(masks_queries_logits[0, 0, :3, :3], expected_slice, rtol=TOLERANCE, atol=TOLERANCE)
# class_queries_logits
class_queries_logits = outputs.class_queries_logits
self.assertEqual(
class_queries_logits.shape, (1, model.config.decoder_config.num_queries, model.config.num_labels + 1)
)
expected_slice = torch.tensor(
[
[4.7177, -3.2586, -2.8853],
[6.6845, -2.9186, -1.2491],
[7.2443, -2.2760, -2.1858],
]
).to(torch_device)
expectations = Expectations(
{
(None, None): [
[-0.9000, -2.6283, -4.5964],
[-3.4123, -5.7789, -8.7919],
[-4.9132, -7.6444, -10.7557],
],
("cuda", 8): [
[4.7177, -3.2586, -2.8853],
[6.6845, -2.9186, -1.2491],
[7.2443, -2.2760, -2.1858],
],
}
)
expected_slice = torch.tensor(expectations.get_expectation()).to(torch_device)
torch.testing.assert_close(
outputs.class_queries_logits[0, :3, :3], expected_slice, rtol=TOLERANCE, atol=TOLERANCE
)