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test cleanup

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Sam Shleifer committed 2020-09-25 10:13:26 -04:00
1 parent 9ff0d016e8
commit 7ff0aea1d9
3 files changed
+25 -101
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src/transformers/tokenization_blenderbot.py
-1
View File
@@ -60,7 +60,6 @@ BLENDERBOT_90M_PRETRAINED_VOCAB_FILES_MAP = {
def get_pairs(word):
"""Return set of symbol pairs in a word.
Word is represented as tuple of symbols (symbols being variable-length strings).
tests/test_modeling_blenderbot.py
+4 -99
View File
@@ -115,6 +115,8 @@ class BlenderbotTesterMixin(ModelTesterMixin, unittest.TestCase):
model.model.decoder.embed_positions.weight.shape == expected_shape
@unittest.skipUnless(torch_device != "cpu", "3B test too slow on CPU.")
@require_torch
class Blenderbot3BIntegrationTests(unittest.TestCase):
@@ -131,104 +133,7 @@ class Blenderbot3BIntegrationTests(unittest.TestCase):
def tokenizer(self):
return BlenderbotTokenizer.from_pretrained(self.ckpt)
@slow
def test_tokenization_same_as_parlai(self):
# TODO(SS): this can run on CPU
self.assertListEqual(self.tokenizer("sam").input_ids, [268, 343, 2])
@slow
@unittest.skip("This fails.")
def test_forward_3B_same_as_parlai(self):
torch.manual_seed(0)
config = BlenderbotConfig(
d_model=16,
vocab_size=50,
encoder_attention_heads=2,
decoder_attention_heads=2,
encoder_layers=2,
decoder_layers=2,
encoder_ffn_dim=4,
decoder_ffn_dim=4,
variant="prelayernorm",
scale_embedding=True,
normalize_embedding=True,
max_position_embeddings=50,
activation_function="gelu",
static_position_embeddings=True,
dropout=0.1,
)
input_ids = torch.tensor(
[[49, 12, 38, 24, 13, 25, 10, 28, 37, 7, 44, 7, 2, 3]],
dtype=torch.long,
device=torch_device,
)
model = BlenderbotForConditionalGeneration(config).to(torch_device)
model.eval()
# output from parlai model after copying the same blenderbot weight in parlai and setting a manual_seed
expected_logits = torch.tensor(
[
[
[
-1.0000e20,
0.0000e00,
2.6462e-02,
9.7588e-02,
-5.6271e-02,
-1.1409e-01,
-3.3294e-02,
-1.0423e-01,
-4.8363e-02,
-1.2610e-01,
-3.4125e-02,
-2.9841e-02,
8.6975e-02,
2.5547e-02,
2.0425e-03,
-5.9153e-02,
1.4392e-02,
-1.4324e-02,
1.2774e-01,
-5.3284e-02,
-1.5876e-02,
9.1752e-02,
-3.0166e-02,
-3.1726e-02,
9.9600e-02,
1.0991e-01,
8.0946e-03,
3.5396e-03,
-2.5164e-02,
-4.0277e-02,
-3.6360e-02,
7.5158e-02,
4.3379e-02,
1.3465e-01,
-1.3209e-01,
-1.1706e-01,
5.6180e-02,
-3.6239e-02,
6.6490e-02,
4.9879e-02,
1.0979e-02,
-2.7895e-02,
-8.4691e-02,
4.5857e-02,
2.0233e-02,
9.2533e-02,
-6.4260e-02,
-5.0988e-02,
-4.0852e-02,
1.9867e-02,
]
]
],
device=torch_device,
)
decoder_inputs = torch.LongTensor([1]).expand(1, 1).to(torch_device)
logits = model(input_ids, decoder_input_ids=decoder_inputs, return_dict=True)["logits"]
assert torch.allclose(expected_logits, logits, atol=1e-4)
@unittest.skip("This fails.")
@slow
@@ -257,6 +162,7 @@ class Blenderbot3BIntegrationTests(unittest.TestCase):
# 9/24: __start__ I have social anxiety. I feel like I'm going to throw up and I'm sweating and blushing.__end__
@require_torch
class Blenderbot90MIntegrationTests(unittest.TestCase):
ckpt = "facebook/blenderbot-90M"
@@ -272,8 +178,6 @@ class Blenderbot90MIntegrationTests(unittest.TestCase):
def tokenizer(self):
return BlenderbotSmallTokenizer.from_pretrained(self.ckpt)
def test_tokenization_same_as_parlai(self):
assert self.tokenizer("sam").input_ids == [1384]
@unittest.skip("This does not pass. It should be deleted")
def test_forward_90M_same_as_parlai(self):
@@ -377,6 +281,7 @@ class Blenderbot90MIntegrationTests(unittest.TestCase):
]
# tgt_text = "i ' m not sure . i just feel like i ' m going to throw up ."
tgt_text = "i don't know. i just feel like i'm going to throw up. it's not fun."
# FP16: " i don't know. i feel like i'm going to throw up. it's hard for me."
model_inputs = self.tokenizer(src_text, return_tensors="pt").to(torch_device)
generated_ids = self.model.generate(**model_inputs, early_stopping=True)[0]
tests/test_tokenization_blenderbot.py
+21 -1
View File
@@ -18,7 +18,8 @@ import json
import os
import unittest
from transformers.tokenization_blenderbot import VOCAB_FILES_NAMES, BlenderbotSmallTokenizer
from transformers.tokenization_blenderbot import VOCAB_FILES_NAMES, BlenderbotSmallTokenizer, BlenderbotTokenizer
from transformers.file_utils import cached_property
from .test_tokenization_common import TokenizerTesterMixin
@@ -66,8 +67,27 @@ class BlenderbotSmallTokenizerTest(TokenizerTesterMixin, unittest.TestCase):
def test_special_tokens_small_tok(self):
tok = BlenderbotSmallTokenizer.from_pretrained("facebook/blenderbot-90M")
assert tok("sam").input_ids == [1384]
src_text = "I am a small frog."
encoded = tok([src_text], padding=False, truncation=False)["input_ids"]
decoded = tok.batch_decode(encoded, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
assert src_text != decoded # I wish it did!
assert decoded == "i am a small frog ."
class Blenderbot3BTokenizerTests(unittest.TestCase):
@cached_property
def tokenizer_3b(self):
return BlenderbotTokenizer.from_pretrained("facebook/blenderbot-3B")
def test_special_tokens_3B_tok(self):
tok = self.tokenizer_3b
src_text = " I am a small frog."
encoded = tok([src_text], padding=False, truncation=False)["input_ids"]
decoded = tok.batch_decode(encoded, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
assert src_text == decoded # I wish it did!
import ipdb; ipdb.set_trace()
def test_3B_tokenization_same_as_parlai(self):
# TODO(SS): this can run on CPU
tok = self.tokenizer_3b
self.assertListEqual(tok(["sam"]).input_ids[0], [268, 343, 2])