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Added mtl to quickstart #1640

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merged 5 commits into from
Jun 5, 2023
Merged

Added mtl to quickstart #1640

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3f7d2d1
Update test_quick_start.py
dimakarp1996 Apr 11, 2023
cb617ed
fix: mt tests
IgnatovFedor May 26, 2023
348aa27
fix: removed overrides from multitask transformer
IgnatovFedor May 26, 2023
0263c52
fix: correct infer_api payload
IgnatovFedor May 29, 2023
fef330e
refactor: re payload
IgnatovFedor Jun 5, 2023
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3 changes: 2 additions & 1 deletion deeppavlov/configs/multitask/mt_glue.json
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Original file line number Diff line number Diff line change
Expand Up @@ -267,7 +267,8 @@
"log_every_n_epochs": 1,
"show_examples": false,
"evaluation_targets": ["valid"],
"class_name": "torch_trainer"
"class_name": "torch_trainer",
"pytest_max_batches": 2
},
"metadata": {
"variables": {
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3 changes: 2 additions & 1 deletion deeppavlov/configs/multitask/multitask_example.json
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Expand Up @@ -219,7 +219,8 @@
"log_every_n_epochs": 1,
"show_examples": false,
"evaluation_targets": ["valid"],
"class_name": "torch_trainer"
"class_name": "torch_trainer",
"pytest_max_batches": 2
},
"metadata": {
"variables": {
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3 changes: 0 additions & 3 deletions deeppavlov/models/torch_bert/multitask_transformer.py
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Expand Up @@ -20,7 +20,6 @@
import numpy as np
import torch
import torch.nn as nn
from overrides import overrides
from torch.nn import CrossEntropyLoss, MSELoss, BCEWithLogitsLoss
from transformers import AutoConfig, AutoModel

Expand Down Expand Up @@ -342,7 +341,6 @@ def __init__(
def _reset_cache(self):
self.preds_cache = {index_: None for index_ in self.types_to_cache if index_ != -1}

@overrides
def init_from_opt(self) -> None:
"""
Initialize from scratch `self.model` with the architecture built
Expand Down Expand Up @@ -401,7 +399,6 @@ def get_decay_params(model): return [
torch.optim.lr_scheduler, self.lr_scheduler_name
)(self.optimizer, **self.lr_scheduler_parameters)

@overrides
def load(self, fname: Optional[str] = None) -> None:
"""
Loads weights.
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21 changes: 12 additions & 9 deletions tests/test_quick_start.py
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Expand Up @@ -138,6 +138,12 @@
("russian_super_glue/russian_superglue_parus_rubert.json", "russian_super_glue", ('IP',)): [LIST_ARGUMENTS_INFER_CHECK],
("russian_super_glue/russian_superglue_rucos_rubert.json", "russian_super_glue", ('IP',)): [RECORD_ARGUMENTS_INFER_CHECK]
},
"multitask":{
("multitask/multitask_example.json", "multitask", ALL_MODES): [
('Dummy text',) + (('Dummy text', 'Dummy text'),) * 3 + ('Dummy text',) + (None,)],
("multitask/mt_glue.json", "multitask", ALL_MODES): [
('Dummy text',) * 2 + (('Dummy text', 'Dummy text'),) * 6 + (None,)]
},
"entity_extraction": {
("entity_extraction/entity_detection_en.json", "entity_extraction", ('IP',)):
[
Expand Down Expand Up @@ -399,7 +405,8 @@ def infer(config_path, qr_list=None, check_outputs=True):
raise RuntimeError(f'Unexpected results for {config_path}: {errors}')

@staticmethod
def infer_api(config_path):
def infer_api(config_path, qr_list):
*inputs, expected_outputs = zip(*qr_list)
server_params = get_server_params(config_path)

url_base = 'http://{}:{}'.format(server_params['host'], api_port or server_params['port'])
Expand All @@ -422,14 +429,10 @@ def infer_api(config_path):
assert response_code == 200, f"GET /api request returned error code {response_code} with {config_path}"

model_args_names = get_response.json()['in']
post_payload = dict()
for arg_name in model_args_names:
arg_value = ' '.join(['qwerty'] * 10)
post_payload[arg_name] = [arg_value]
post_payload = dict(zip(model_args_names, inputs))
# TODO: remove this if from here and socket
if 'parus' in str(config_path):
post_payload = {k: [v] for k, v in post_payload.items()}

if 'docred' in str(config_path) or 'rured' in str(config_path):
post_payload = {k: v[0] for k, v in post_payload.items()}
post_response = requests.post(url, json=post_payload, headers=post_headers)
response_code = post_response.status_code
assert response_code == 200, f"POST request returned error code {response_code} with {config_path}"
Expand Down Expand Up @@ -519,7 +522,7 @@ def test_inferring_pretrained_model(self, model, conf_file, model_dir, mode):

def test_inferring_pretrained_model_api(self, model, conf_file, model_dir, mode):
if 'IP' in mode:
self.infer_api(test_configs_path / conf_file)
self.infer_api(test_configs_path / conf_file, PARAMS[model][(conf_file, model_dir, mode)])
else:
pytest.skip("Unsupported mode: {}".format(mode))

Expand Down