From 52ed6d4fe6abaead4a9bceceb1f34ce357c64b14 Mon Sep 17 00:00:00 2001 From: harshaljanjani Date: Fri, 6 Feb 2026 16:38:03 +0400 Subject: [PATCH] fix(testing): Small test-only fixes for CLAP, BLOOM, and CLVP --- tests/models/bloom/test_modeling_bloom.py | 4 ++-- tests/models/clap/test_modeling_clap.py | 16 ++++++++++++---- tests/models/clvp/test_modeling_clvp.py | 1 + 3 files changed, 15 insertions(+), 6 deletions(-) diff --git a/tests/models/bloom/test_modeling_bloom.py b/tests/models/bloom/test_modeling_bloom.py index ba6c73d4f1bd..a6b3f7ed662d 100644 --- a/tests/models/bloom/test_modeling_bloom.py +++ b/tests/models/bloom/test_modeling_bloom.py @@ -544,7 +544,7 @@ def test_batch_generation(self): input_sentence = ["I enjoy walking with my cute dog", "I enjoy walking with my cute dog"] - inputs = tokenizer.batch_encode_plus(input_sentence, return_tensors="pt", padding=True) + inputs = tokenizer(input_sentence, return_tensors="pt", padding=True) input_ids = inputs["input_ids"].to(torch_device) attention_mask = inputs["attention_mask"] greedy_output = model.generate(input_ids, attention_mask=attention_mask, max_length=50, do_sample=False) @@ -565,7 +565,7 @@ def test_batch_generation_padding(self): input_sentence = ["I enjoy walking with my cute dog", "Hello my name is"] input_sentence_without_pad = "Hello my name is" - input_ids = tokenizer.batch_encode_plus(input_sentence, return_tensors="pt", padding=True) + input_ids = tokenizer(input_sentence, return_tensors="pt", padding=True) input_ids_without_pad = tokenizer.encode(input_sentence_without_pad, return_tensors="pt") input_ids, attention_mask = input_ids["input_ids"].to(torch_device), input_ids["attention_mask"] diff --git a/tests/models/clap/test_modeling_clap.py b/tests/models/clap/test_modeling_clap.py index 3791011c7ee3..fa6a197d7c31 100644 --- a/tests/models/clap/test_modeling_clap.py +++ b/tests/models/clap/test_modeling_clap.py @@ -538,7 +538,9 @@ def test_integration_unfused(self): expected_mean = EXPECTED_MEANS_UNFUSED[padding] self.assertTrue( - torch.allclose(audio_embed.cpu().mean(), torch.tensor([expected_mean]), atol=1e-3, rtol=1e-3) + torch.allclose( + audio_embed.pooler_output.cpu().mean(), torch.tensor([expected_mean]), atol=1e-3, rtol=1e-3 + ) ) def test_integration_fused(self): @@ -565,7 +567,9 @@ def test_integration_fused(self): expected_mean = EXPECTED_MEANS_FUSED[padding] self.assertTrue( - torch.allclose(audio_embed.cpu().mean(), torch.tensor([expected_mean]), atol=1e-3, rtol=1e-3) + torch.allclose( + audio_embed.pooler_output.cpu().mean(), torch.tensor([expected_mean]), atol=1e-3, rtol=1e-3 + ) ) def test_batched_fused(self): @@ -592,7 +596,9 @@ def test_batched_fused(self): expected_mean = EXPECTED_MEANS_FUSED[padding] self.assertTrue( - torch.allclose(audio_embed.cpu().mean(), torch.tensor([expected_mean]), atol=1e-3, rtol=1e-3) + torch.allclose( + audio_embed.pooler_output.cpu().mean(), torch.tensor([expected_mean]), atol=1e-3, rtol=1e-3 + ) ) def test_batched_unfused(self): @@ -617,5 +623,7 @@ def test_batched_unfused(self): expected_mean = EXPECTED_MEANS_FUSED[padding] self.assertTrue( - torch.allclose(audio_embed.cpu().mean(), torch.tensor([expected_mean]), atol=1e-3, rtol=1e-3) + torch.allclose( + audio_embed.pooler_output.cpu().mean(), torch.tensor([expected_mean]), atol=1e-3, rtol=1e-3 + ) ) diff --git a/tests/models/clvp/test_modeling_clvp.py b/tests/models/clvp/test_modeling_clvp.py index 644f78cda5e5..29ba5af8f49e 100644 --- a/tests/models/clvp/test_modeling_clvp.py +++ b/tests/models/clvp/test_modeling_clvp.py @@ -321,6 +321,7 @@ class ClvpModelForConditionalGenerationTester: def __init__(self, parent, is_training=False): self.parent = parent self.clvp_encoder_tester = ClvpEncoderTester(parent) + self.text_model_tester = self.clvp_encoder_tester self.is_training = is_training self.batch_size = self.clvp_encoder_tester.batch_size # need bs for batching_equivalence test