def main():
try:
# Get configuration settings
form_endpoint = "https://doors1.cognitiveservices.azure.com/"
form_key = "70b2796924584d8da912296e8dea613a"
trainingDataUrl = "https://doors.blob.core.windows.net/treinamento?sp=racwdl&st=2021-05-27T23:44:21Z&se=2021-08-02T07:44:21Z&sv=2020-02-10&sr=c&sig=9Tq5HVWS6Fzq5mHIIklZk3Z1wO%2B5junlwtlNTIFP194%3D"
# Authenticate Form Training Client
form_recognizer_client = FormRecognizerClient(
form_endpoint, AzureKeyCredential(form_key))
form_training_client = FormTrainingClient(form_endpoint,
AzureKeyCredential(form_key))
# Train model
poller = form_training_client.begin_training(trainingDataUrl,
use_training_labels=False)
model = poller.result()
print("Model ID: {}".format(model.model_id))
print("Status: {}".format(model.status))
print("Training started on: {}".format(model.training_started_on))
print("Training completed on: {}".format(model.training_completed_on))
except Exception as ex:
print(ex)
def test_training_auth_bad_key(self, resource_group, location,
form_recognizer_account,
form_recognizer_account_key):
client = FormTrainingClient(form_recognizer_account,
AzureKeyCredential("xxxx"))
with self.assertRaises(ClientAuthenticationError):
poller = client.begin_training("xx", use_training_labels=False)
def test_api_version_form_training_client(self, resource_group, location, form_recognizer_account, form_recognizer_account_key):
with self.assertRaises(ValueError):
ftc = FormTrainingClient(endpoint=form_recognizer_account, credential=AzureKeyCredential(form_recognizer_account_key), api_version="v9.1")
# these do not raise
ftc = FormTrainingClient(endpoint=form_recognizer_account, credential=AzureKeyCredential(form_recognizer_account_key), api_version="v2.0")
ftc = FormTrainingClient(endpoint=form_recognizer_account, credential=AzureKeyCredential(form_recognizer_account_key), api_version=FormRecognizerApiVersion.V2_0)
def train_model_with_labels(self):
from azure.ai.formrecognizer import FormTrainingClient
from azure.core.credentials import AzureKeyCredential
form_training_client = FormTrainingClient(self.endpoint,
AzureKeyCredential(self.key))
poller = form_training_client.begin_train_model(
self.container_sas_url, use_training_labels=True)
model = poller.result()
# Custom model information
print("Model ID: {}".format(model.model_id))
print("Status: {}".format(model.status))
print("Requested on: {}".format(model.requested_on))
print("Completed on: {}".format(model.completed_on))
print("Recognized fields:")
# looping through the submodels, which contains the fields they were trained on
# The labels are based on the ones you gave the training document.
for submodel in model.submodels:
print("...The submodel with form type {} has accuracy '{}'".format(
submodel.form_type, submodel.accuracy))
for name, field in submodel.fields.items():
print(
"...The model found field '{}' to have name '{}' with an accuracy of {}"
.format(name, field.name, field.accuracy))
# Training result information
for doc in model.training_documents:
print("Document name: {}".format(doc.document_name))
print("Document status: {}".format(doc.status))
print("Document page count: {}".format(doc.page_count))
print("Document errors: {}".format(doc.errors))
def train_model_without_labels(self):
# [START training]
from azure.ai.formrecognizer import FormTrainingClient
from azure.core.credentials import AzureKeyCredential
form_training_client = FormTrainingClient(self.endpoint,
AzureKeyCredential(self.key))
# Default for begin_train_model is `use_training_labels=False`
poller = form_training_client.begin_train_model(
self.container_sas_url, use_training_labels=False)
model = poller.result()
# Custom model information
print("Model ID: {}".format(model.model_id))
print("Status: {}".format(model.status))
print("Requested on: {}".format(model.requested_on))
print("Completed on: {}".format(model.completed_on))
print("Recognized fields:")
# Looping through the submodels, which contains the fields they were trained on
for submodel in model.submodels:
print("...The submodel has form type '{}'".format(
submodel.form_type))
for name, field in submodel.fields.items():
print(
"...The model found field '{}' to have label '{}'".format(
name, field.label))
# [END training]
# Training result information
for doc in model.training_documents:
print("Document name: {}".format(doc.document_name))
print("Document status: {}".format(doc.status))
print("Document page count: {}".format(doc.page_count))
print("Document errors: {}".format(doc.errors))
def test_account_properties_auth_bad_key(self, resource_group, location,
form_recognizer_account,
form_recognizer_account_key):
client = FormTrainingClient(form_recognizer_account,
AzureKeyCredential("xxxx"))
with self.assertRaises(ClientAuthenticationError):
result = client.get_account_properties()
def test_delete_model_auth_bad_key(self, resource_group, location,
form_recognizer_account,
form_recognizer_account_key):
client = FormTrainingClient(form_recognizer_account,
AzureKeyCredential("xxxx"))
with self.assertRaises(ClientAuthenticationError):
client.delete_model("xx")
async def test_get_form_recognizer_client(self,
formrecognizer_test_endpoint,
formrecognizer_test_api_key,
**kwargs):
# this can be reverted to set_bodiless_matcher() after tests are re-recorded and don't contain these headers
set_custom_default_matcher(
compare_bodies=False,
excluded_headers=
"Authorization,Content-Length,x-ms-client-request-id,x-ms-request-id"
)
transport = AioHttpTransport()
ftc = FormTrainingClient(
endpoint=formrecognizer_test_endpoint,
credential=AzureKeyCredential(formrecognizer_test_api_key),
transport=transport,
api_version="2.1")
async with ftc:
await ftc.get_account_properties()
assert transport.session is not None
async with ftc.get_form_recognizer_client() as frc:
assert transport.session is not None
await (await frc.begin_recognize_receipts_from_url(
self.receipt_url_jpg)).wait()
await ftc.get_account_properties()
assert transport.session is not None
def main():
try:
# Get configuration settings
load_dotenv()
form_endpoint = os.getenv('FORM_ENDPOINT')
form_key = os.getenv('FORM_KEY')
trainingDataUrl = os.getenv('STORAGE_URL')
# Authenticate Form Training Client
form_recognizer_client = FormRecognizerClient(
form_endpoint, AzureKeyCredential(form_key))
form_training_client = FormTrainingClient(form_endpoint,
AzureKeyCredential(form_key))
# Train model
poller = form_training_client.begin_training(trainingDataUrl,
use_training_labels=False)
model = poller.result()
print("Model ID: {}".format(model.model_id))
print("Status: {}".format(model.status))
print("Training started on: {}".format(model.training_started_on))
print("Training completed on: {}".format(model.training_completed_on))
except Exception as ex:
print(ex)
def test_api_version_form_training_client(self, formrecognizer_test_endpoint, formrecognizer_test_api_key):
with self.assertRaises(ValueError):
ftc = FormTrainingClient(endpoint=formrecognizer_test_endpoint, credential=AzureKeyCredential(formrecognizer_test_api_key), api_version="9.1")
# these do not raise
ftc = FormTrainingClient(endpoint=formrecognizer_test_endpoint, credential=AzureKeyCredential(formrecognizer_test_api_key), api_version="2.0")
ftc = FormTrainingClient(endpoint=formrecognizer_test_endpoint, credential=AzureKeyCredential(formrecognizer_test_api_key), api_version=FormRecognizerApiVersion.V2_0)
def train_model_without_labels(self):
# [START training]
from azure.ai.formrecognizer import FormTrainingClient
from azure.core.credentials import AzureKeyCredential
endpoint = os.environ["AZURE_FORM_RECOGNIZER_ENDPOINT"]
key = os.environ["AZURE_FORM_RECOGNIZER_KEY"]
container_sas_url = os.environ["CONTAINER_SAS_URL"]
form_training_client = FormTrainingClient(endpoint, AzureKeyCredential(key))
poller = form_training_client.begin_training(container_sas_url, use_training_labels=False)
model = poller.result()
# Custom model information
print("Model ID: {}".format(model.model_id))
print("Status: {}".format(model.status))
print("Model name: {}".format(model.model_name))
print("Training started on: {}".format(model.training_started_on))
print("Training completed on: {}".format(model.training_completed_on))
print("Recognized fields:")
# Looping through the submodels, which contains the fields they were trained on
for submodel in model.submodels:
print("...The submodel has form type '{}'".format(submodel.form_type))
for name, field in submodel.fields.items():
print("...The model found field '{}' to have label '{}'".format(
name, field.label
))
# [END training]
# Training result information
for doc in model.training_documents:
print("Document name: {}".format(doc.name))
print("Document status: {}".format(doc.status))
print("Document page count: {}".format(doc.page_count))
print("Document errors: {}".format(doc.errors))
def manage_custom_models(self):
from azure.core.credentials import AzureKeyCredential
from azure.core.exceptions import ResourceNotFoundError
from azure.ai.formrecognizer import FormTrainingClient
endpoint = os.environ["AZURE_FORM_RECOGNIZER_ENDPOINT"]
key = os.environ["AZURE_FORM_RECOGNIZER_KEY"]
container_sas_url = os.environ["CONTAINER_SAS_URL_V2"]
# [START get_account_properties]
form_training_client = FormTrainingClient(
endpoint=endpoint, credential=AzureKeyCredential(key))
# First, we see how many custom models we have, and what our limit is
account_properties = form_training_client.get_account_properties()
print(
"Our account has {} custom models, and we can have at most {} custom models\n"
.format(account_properties.custom_model_count,
account_properties.custom_model_limit))
# [END get_account_properties]
# Next, we get a paged list of all of our custom models
# [START list_custom_models]
custom_models = form_training_client.list_custom_models()
print("We have models with the following IDs:")
for model in custom_models:
print(model.model_id)
# [END list_custom_models]
# let's train a model to use for this sample
poller = form_training_client.begin_training(container_sas_url,
use_training_labels=False)
model = poller.result()
# Now we'll get information for the model we just trained
# [START get_custom_model]
custom_model = form_training_client.get_custom_model(
model_id=model.model_id)
print("\nModel ID: {}".format(custom_model.model_id))
print("Status: {}".format(custom_model.status))
print("Model name: {}".format(custom_model.model_name))
print("Is this a composed model?: {}".format(
custom_model.properties.is_composed_model))
print("Training started on: {}".format(
custom_model.training_started_on))
print("Training completed on: {}".format(
custom_model.training_completed_on))
# [END get_custom_model]
# Finally, we will delete this model by ID
# [START delete_model]
form_training_client.delete_model(model_id=custom_model.model_id)
try:
form_training_client.get_custom_model(
model_id=custom_model.model_id)
except ResourceNotFoundError:
print("Successfully deleted model with id {}".format(
custom_model.model_id))
def test_delete_model_empty_model_id(self, resource_group, location,
form_recognizer_account,
form_recognizer_account_key):
client = FormTrainingClient(
form_recognizer_account,
AzureKeyCredential(form_recognizer_account_key))
with self.assertRaises(ValueError):
result = client.delete_model("")
def test_get_model_none_model_id(self, resource_group, location,
form_recognizer_account,
form_recognizer_account_key):
client = FormTrainingClient(
form_recognizer_account,
AzureKeyCredential(form_recognizer_account_key))
with self.assertRaises(ValueError):
result = client.get_custom_model(None)
def test_sample_recognize_custom_forms(self, resource_group, location, form_recognizer_account, form_recognizer_account_key):
_setenv('CONTAINER_SAS_URL', 'AZURE_FORM_RECOGNIZER_STORAGE_CONTAINER_SAS_URL')
ftc = FormTrainingClient(form_recognizer_account, AzureKeyCredential(form_recognizer_account_key))
container_sas_url = os.environ['CONTAINER_SAS_URL']
poller = ftc.begin_training(container_sas_url, use_training_labels=False)
model = poller.result()
os.environ['CUSTOM_TRAINED_MODEL_ID'] = model.model_id
_test_file('sample_recognize_custom_forms.py', form_recognizer_account, form_recognizer_account_key)
def test_list_model_auth_bad_key(self, resource_group, location,
form_recognizer_account,
form_recognizer_account_key):
client = FormTrainingClient(form_recognizer_account,
AzureKeyCredential("xxxx"))
with self.assertRaises(ClientAuthenticationError):
result = client.list_custom_models()
for res in result:
test = res
def test_account_properties(self, resource_group, location,
form_recognizer_account,
form_recognizer_account_key):
client = FormTrainingClient(
form_recognizer_account,
AzureKeyCredential(form_recognizer_account_key))
properties = client.get_account_properties()
self.assertIsNotNone(properties.custom_model_limit)
self.assertIsNotNone(properties.custom_model_count)
def authentication_with_api_key_credential_form_training_client(self):
# [START create_ft_client_with_key]
from azure.core.credentials import AzureKeyCredential
from azure.ai.formrecognizer import FormTrainingClient
endpoint = os.environ["AZURE_FORM_RECOGNIZER_ENDPOINT"]
key = os.environ["AZURE_FORM_RECOGNIZER_KEY"]
form_training_client = FormTrainingClient(endpoint, AzureKeyCredential(key))
# [END create_ft_client_with_key]
properties = form_training_client.get_account_properties()
def authentication_with_azure_active_directory_form_training_client(self):
"""DefaultAzureCredential will use the values from these environment
variables: AZURE_CLIENT_ID, AZURE_TENANT_ID, AZURE_CLIENT_SECRET
"""
# [START create_ft_client_with_aad]
from azure.ai.formrecognizer import FormTrainingClient
from azure.identity import DefaultAzureCredential
endpoint = os.environ["AZURE_FORM_RECOGNIZER_ENDPOINT"]
credential = DefaultAzureCredential()
form_training_client = FormTrainingClient(endpoint, credential)
# [END create_ft_client_with_aad]
properties = form_training_client.get_account_properties()
def manage_custom_models(self):
# [START get_account_properties]
from azure.core.credentials import AzureKeyCredential
from azure.core.exceptions import ResourceNotFoundError
from azure.ai.formrecognizer import FormTrainingClient
endpoint = os.environ["AZURE_FORM_RECOGNIZER_ENDPOINT"]
key = os.environ["AZURE_FORM_RECOGNIZER_KEY"]
form_training_client = FormTrainingClient(
endpoint=endpoint, credential=AzureKeyCredential(key))
# First, we see how many custom models we have, and what our limit is
account_properties = form_training_client.get_account_properties()
print(
"Our account has {} custom models, and we can have at most {} custom models\n"
.format(account_properties.custom_model_count,
account_properties.custom_model_limit))
# [END get_account_properties]
# Next, we get a paged list of all of our custom models
# [START list_custom_models]
custom_models = form_training_client.list_custom_models()
print("We have models with the following IDs:")
# Let's pull out the first model
first_model = next(custom_models)
print(first_model.model_id)
for model in custom_models:
print(model.model_id)
# [END list_custom_models]
# Now we'll get information for the first custom model in the paged list
# [START get_custom_model]
custom_model = form_training_client.get_custom_model(
model_id=first_model.model_id)
print("\nModel ID: {}".format(custom_model.model_id))
print("Status: {}".format(custom_model.status))
print("Training started on: {}".format(
custom_model.training_started_on))
print("Training completed on: {}".format(
custom_model.training_completed_on))
# [END get_custom_model]
# Finally, we will delete this model by ID
# [START delete_model]
form_training_client.delete_model(model_id=custom_model.model_id)
try:
form_training_client.get_custom_model(
model_id=custom_model.model_id)
except ResourceNotFoundError:
print("Successfully deleted model with id {}".format(
custom_model.model_id))
def main():
try:
# Get configuration settings
load_dotenv()
form_endpoint = os.getenv('FORM_ENDPOINT')
form_key = os.getenv('FORM_KEY')
# To train a model you need your Blob URI to access your training files
trainingDataUrl = os.getenv('STORAGE_URL')
# Create client using endpoint and key
form_recognizer_client = FormRecognizerClient(
form_endpoint, AzureKeyCredential(form_key))
form_training_client = FormTrainingClient(form_endpoint,
AzureKeyCredential(form_key))
# Use Training Labels = False
poller = form_training_client.begin_training(trainingDataUrl,
use_training_labels=False)
model = poller.result()
print("Model ID: {}".format(model.model_id))
print("Status: {}".format(model.status))
print("Training started on: {}".format(model.training_started_on))
print("Training completed on: {}".format(model.training_completed_on))
print("\nRecognized fields:")
for submodel in model.submodels:
print(
"The submodel with form type '{}' has recognized the following fields: {}"
.format(
submodel.form_type,
", ".join([
field.label if field.label else name
for name, field in submodel.fields.items()
]),
))
# Training result information
for doc in model.training_documents:
print("Document name: {}".format(doc.name))
print("Document status: {}".format(doc.status))
print("Document page count: {}".format(doc.page_count))
print("Document errors: {}".format(doc.errors))
except Exception as ex:
print(ex)
def test_logging_info_ft_client(self, resource_group, location, form_recognizer_account, form_recognizer_account_key):
client = FormTrainingClient(form_recognizer_account, AzureKeyCredential(form_recognizer_account_key))
mock_handler = MockHandler()
logger = logging.getLogger("azure")
logger.addHandler(mock_handler)
logger.setLevel(logging.INFO)
result = client.get_account_properties()
for message in mock_handler.messages:
if message.levelname == "INFO":
# not able to use json.loads here. At INFO level only API key should be REDACTED
if message.message.find("Ocp-Apim-Subscription-Key") != -1:
assert message.message.find("REDACTED") != -1
else:
assert message.message.find("REDACTED") == -1
def test_document_api_version_form_training_client(self):
with pytest.raises(ValueError) as excinfo:
client = FormTrainingClient(
"url",
"key",
api_version=DocumentAnalysisApiVersion.V2021_09_30_PREVIEW)
assert "Unsupported API version '2021-09-30-preview'. Please select from: {}\nAPI version '2021-09-30-preview' is " \
"only available for DocumentAnalysisClient and DocumentModelAdministrationClient.".format(
", ".join(v.value for v in FormRecognizerApiVersion)) == str(excinfo.value)
def train_model_with_labels(self):
from azure.ai.formrecognizer import FormTrainingClient
from azure.core.credentials import AzureKeyCredential
endpoint = os.environ["AZURE_FORM_RECOGNIZER_ENDPOINT"]
key = os.environ["AZURE_FORM_RECOGNIZER_KEY"]
container_sas_url = os.environ["CONTAINER_SAS_URL"]
form_training_client = FormTrainingClient(endpoint,
AzureKeyCredential(key))
poller = form_training_client.begin_training(container_sas_url,
use_training_labels=True,
model_name="mymodel")
model = poller.result()
# Custom model information
print("Model ID: {}".format(model.model_id))
print("Status: {}".format(model.status))
print("Model name: {}".format(model.model_name))
print("Is this a composed model?: {}".format(
model.properties.is_composed_model))
print("Training started on: {}".format(model.training_started_on))
print("Training completed on: {}".format(model.training_completed_on))
print("Recognized fields:")
# looping through the submodels, which contains the fields they were trained on
# The labels are based on the ones you gave the training document.
for submodel in model.submodels:
print("...The submodel has model ID: {}".format(submodel.model_id))
print(
"...The submodel with form type {} has an average accuracy '{}'"
.format(submodel.form_type, submodel.accuracy))
for name, field in submodel.fields.items():
print(
"...The model found the field '{}' with an accuracy of {}".
format(name, field.accuracy))
# Training result information
for doc in model.training_documents:
print("Document name: {}".format(doc.name))
print("Document status: {}".format(doc.status))
print("Document page count: {}".format(doc.page_count))
print("Document errors: {}".format(doc.errors))
async def test_get_form_recognizer_client(self,
formrecognizer_test_endpoint,
formrecognizer_test_api_key):
transport = AioHttpTransport()
ftc = FormTrainingClient(
endpoint=formrecognizer_test_endpoint,
credential=AzureKeyCredential(formrecognizer_test_api_key),
transport=transport,
api_version="2.1")
async with ftc:
await ftc.get_account_properties()
assert transport.session is not None
async with ftc.get_form_recognizer_client() as frc:
assert transport.session is not None
await (await frc.begin_recognize_receipts_from_url(
self.receipt_url_jpg)).wait()
await ftc.get_account_properties()
assert transport.session is not None
def test_sample_differentiate_output_models_trained_with_and_without_labels(
self, resource_group, location, form_recognizer_account,
form_recognizer_account_key):
os.environ['CONTAINER_SAS_URL'] = self.get_settings_value(
"FORM_RECOGNIZER_STORAGE_CONTAINER_SAS_URL")
ftc = FormTrainingClient(
form_recognizer_account,
AzureKeyCredential(form_recognizer_account_key))
container_sas_url = os.environ['CONTAINER_SAS_URL']
poller = ftc.begin_training(container_sas_url,
use_training_labels=False)
unlabeled_model = poller.result()
poller = ftc.begin_training(container_sas_url,
use_training_labels=True)
labeled_model = poller.result()
os.environ["ID_OF_MODEL_TRAINED_WITH_LABELS"] = labeled_model.model_id
os.environ[
"ID_OF_MODEL_TRAINED_WITHOUT_LABELS"] = unlabeled_model.model_id
_test_file(
'sample_differentiate_output_models_trained_with_and_without_labels.py',
form_recognizer_account, form_recognizer_account_key)
def copy_model(self):
from azure.core.credentials import AzureKeyCredential
from azure.ai.formrecognizer import FormTrainingClient
source_endpoint = os.environ["AZURE_FORM_RECOGNIZER_ENDPOINT"]
source_key = os.environ["AZURE_FORM_RECOGNIZER_KEY"]
target_endpoint = os.environ["AZURE_FORM_RECOGNIZER_TARGET_ENDPOINT"]
target_key = os.environ["AZURE_FORM_RECOGNIZER_TARGET_KEY"]
source_model_id = os.environ["AZURE_SOURCE_MODEL_ID"]
target_region = os.environ["AZURE_FORM_RECOGNIZER_TARGET_REGION"]
target_resource_id = os.environ[
"AZURE_FORM_RECOGNIZER_TARGET_RESOURCE_ID"]
# [START get_copy_authorization]
target_client = FormTrainingClient(
endpoint=target_endpoint,
credential=AzureKeyCredential(target_key))
target = target_client.get_copy_authorization(
resource_region=target_region, resource_id=target_resource_id)
# [END get_copy_authorization]
# [START begin_copy_model]
source_client = FormTrainingClient(
endpoint=source_endpoint,
credential=AzureKeyCredential(source_key))
poller = source_client.begin_copy_model(model_id=source_model_id,
target=target)
copied_over_model = poller.result()
print("Model ID: {}".format(copied_over_model.model_id))
print("Status: {}".format(copied_over_model.status))
def test_get_form_recognizer_client(self, resource_group, location, form_recognizer_account, form_recognizer_account_key):
transport = RequestsTransport()
ftc = FormTrainingClient(endpoint=form_recognizer_account, credential=AzureKeyCredential(form_recognizer_account_key), transport=transport)
with ftc:
ftc.get_account_properties()
assert transport.session is not None
with ftc.get_form_recognizer_client() as frc:
assert transport.session is not None
frc.begin_recognize_receipts_from_url(self.receipt_url_jpg).wait()
ftc.get_account_properties()
assert transport.session is not None
def test_get_form_recognizer_client_v2(self, formrecognizer_test_endpoint, formrecognizer_test_api_key):
transport = RequestsTransport()
ftc = FormTrainingClient(endpoint=formrecognizer_test_endpoint, credential=AzureKeyCredential(formrecognizer_test_api_key), transport=transport, api_version="2.1")
with ftc:
ftc.get_account_properties()
assert transport.session is not None
with ftc.get_form_recognizer_client() as frc:
assert transport.session is not None
frc.begin_recognize_receipts_from_url(self.receipt_url_jpg).wait()
assert frc._api_version == FormRecognizerApiVersion.V2_1
ftc.get_account_properties()
assert transport.session is not None
def test_sample_copy_model(self, resource_group, location,
form_recognizer_account,
form_recognizer_account_key):
os.environ['CONTAINER_SAS_URL'] = self.get_settings_value(
"FORM_RECOGNIZER_STORAGE_CONTAINER_SAS_URL")
ftc = FormTrainingClient(
form_recognizer_account,
AzureKeyCredential(form_recognizer_account_key))
container_sas_url = os.environ['CONTAINER_SAS_URL']
poller = ftc.begin_training(container_sas_url,
use_training_labels=False)
model = poller.result()
os.environ['AZURE_SOURCE_MODEL_ID'] = model.model_id
os.environ[
"AZURE_FORM_RECOGNIZER_TARGET_ENDPOINT"] = form_recognizer_account
os.environ[
"AZURE_FORM_RECOGNIZER_TARGET_KEY"] = form_recognizer_account_key
os.environ["AZURE_FORM_RECOGNIZER_TARGET_REGION"] = location
os.environ["AZURE_FORM_RECOGNIZER_TARGET_RESOURCE_ID"] = \
"/subscriptions/" + self.get_settings_value("SUBSCRIPTION_ID") + "/resourceGroups/" + \
resource_group.name + "/providers/Microsoft.CognitiveServices/accounts/" + \
FormRecognizerTest._FORM_RECOGNIZER_NAME
_test_file('sample_copy_model.py', form_recognizer_account,
form_recognizer_account_key)