def data_impl(self, request):
"""Retrieves and processes the tool data for a run and a host.
Args:
request: XMLHttpRequest
Returns:
A string that can be served to the frontend tool or None if tool,
run or host is invalid.
"""
run = request.args.get('run')
tool = request.args.get('tag')
host = request.args.get('host')
run_dir = self._run_dir(run)
# Profile plugin "run" is the last component of run dir.
profile_run = os.path.basename(run_dir)
if tool not in TOOLS:
return None
self.start_grpc_stub_if_necessary()
if tool == 'trace_viewer@' and self.stub is not None:
from tensorflow.core.profiler import profiler_analysis_pb2
grpc_request = profiler_analysis_pb2.ProfileSessionDataRequest()
grpc_request.repository_root = os.path.dirname(run_dir)
grpc_request.session_id = profile_run
grpc_request.tool_name = 'trace_viewer'
# Remove the trailing dot if present
grpc_request.host_name = host.rstrip('.')
grpc_request.parameters['resolution'] = request.args.get('resolution')
if request.args.get('start_time_ms') is not None:
grpc_request.parameters['start_time_ms'] = request.args.get(
'start_time_ms')
if request.args.get('end_time_ms') is not None:
grpc_request.parameters['end_time_ms'] = request.args.get('end_time_ms')
grpc_response = self.stub.GetSessionToolData(grpc_request)
return grpc_response.output
if tool not in TOOLS:
return None
tool_name = str(host) + TOOLS[tool]
asset_path = os.path.join(run_dir, tool_name)
raw_data = None
try:
with tf.io.gfile.GFile(asset_path, 'rb') as f:
raw_data = f.read()
except tf.errors.NotFoundError:
logger.warn('Asset path %s not found', asset_path)
except tf.errors.OpError as e:
logger.warn("Couldn't read asset path: %s, OpError %s", asset_path, e)
if raw_data is None:
return None
if tool == 'trace_viewer':
return process_raw_trace(raw_data)
if tool in _RAW_DATA_TOOLS:
return raw_data
return None
def data_impl(self, request):
"""Retrieves and processes the tool data for a run and a host.
Args:
request: XMLHttpRequest
Returns:
A string that can be served to the frontend tool or None if tool,
run or host is invalid.
"""
run = request.args.get('run')
tool = request.args.get('tag')
host = request.args.get('host')
tqx = request.args.get('tqx')
run_dir = self._run_dir(run)
# Profile plugin "run" is the last component of run dir.
profile_run = os.path.basename(run_dir)
if tool not in TOOLS and not _use_xplane(tool):
return None, None
self.start_grpc_stub_if_necessary()
if tool == 'trace_viewer@' and self.stub is not None:
# Streaming trace viewer needs profiler_analysis service, which is only
# supported in Cloud TPU. This code is unused when data was produced by
# open-source TensorFlow. Only import the library when needed.
# pylint: disable=g-import-not-at-top
# pylint: disable=g-direct-tensorflow-import
from tensorflow.core.profiler import profiler_analysis_pb2
# pylint: enable=g-import-not-at-top
# pylint: enable=g-direct-tensorflow-import
grpc_request = profiler_analysis_pb2.ProfileSessionDataRequest()
grpc_request.repository_root = os.path.dirname(run_dir)
grpc_request.session_id = profile_run
grpc_request.tool_name = 'trace_viewer'
# Remove the trailing dot if present
grpc_request.host_name = host.rstrip('.')
grpc_request.parameters['resolution'] = request.args.get(
'resolution', 8000)
if request.args.get('start_time_ms') is not None:
grpc_request.parameters['start_time_ms'] = request.args.get(
'start_time_ms')
if request.args.get('end_time_ms') is not None:
grpc_request.parameters['end_time_ms'] = request.args.get(
'end_time_ms')
grpc_response = self.stub.GetSessionToolData(grpc_request)
return grpc_response.output, None
asset_path = os.path.join(run_dir, _make_filename(host, tool))
data, content_encoding = None, None
if _use_xplane(tool):
if host == ALL_HOSTS:
file_pattern = _make_filename('*', 'xplane')
try:
asset_paths = tf.io.gfile.glob(
os.path.join(run_dir, file_pattern))
except tf.errors.OpError as e:
logger.warning(
'Cannot read asset directory: %s, OpError %s', run_dir,
e)
else:
asset_paths = [asset_path]
try:
data = convert.xspace_to_tool_data(asset_paths, tool, tqx)
except AttributeError:
logger.warning(
'XPlane converters are available after Tensorflow 2.4')
return data, content_encoding
raw_data = None
try:
with tf.io.gfile.GFile(asset_path, 'rb') as f:
raw_data = f.read()
except tf.errors.NotFoundError:
logger.warning('Asset path %s not found', asset_path)
except tf.errors.OpError as e:
logger.warning("Couldn't read asset path: %s, OpError %s",
asset_path, e)
if raw_data is None:
return None, None
if tool in _RAW_DATA_TOOLS:
data = raw_data
if tool[-1] == '#':
content_encoding = 'gzip'
else:
data = convert.tool_proto_to_tool_data(raw_data, tool, tqx)
return data, content_encoding
def data_impl(self, request):
"""Retrieves and processes the tool data for a run and a host.
Args:
request: XMLHttpRequest
Returns:
A string that can be served to the frontend tool or None if tool,
run or host is invalid.
"""
run = request.args.get('run')
tool = request.args.get('tag')
host = request.args.get('host')
tqx = request.args.get('tqx')
run_dir = self._run_dir(run)
# Profile plugin "run" is the last component of run dir.
profile_run = os.path.basename(run_dir)
if tool not in TOOLS:
return None, None
self.start_grpc_stub_if_necessary()
if tool == 'trace_viewer@' and self.stub is not None:
# Streaming trace viewer needs profiler_analysis service, which is only
# supported in Cloud TPU. This code is unused when data was produced by
# open-source TensorFlow. Only import the library when needed.
# pylint: disable=g-import-not-at-top
# pylint: disable=g-direct-tensorflow-import
from tensorflow.core.profiler import profiler_analysis_pb2
# pylint: enable=g-import-not-at-top
# pylint: enable=g-direct-tensorflow-import
grpc_request = profiler_analysis_pb2.ProfileSessionDataRequest()
grpc_request.repository_root = os.path.dirname(run_dir)
grpc_request.session_id = profile_run
grpc_request.tool_name = 'trace_viewer'
# Remove the trailing dot if present
grpc_request.host_name = host.rstrip('.')
grpc_request.parameters['resolution'] = request.args.get(
'resolution')
if request.args.get('start_time_ms') is not None:
grpc_request.parameters['start_time_ms'] = request.args.get(
'start_time_ms')
if request.args.get('end_time_ms') is not None:
grpc_request.parameters['end_time_ms'] = request.args.get(
'end_time_ms')
grpc_response = self.stub.GetSessionToolData(grpc_request)
return grpc_response.output, None
asset_path = os.path.join(run_dir, _make_filename(host, tool))
raw_data = None
try:
with tf.io.gfile.GFile(asset_path, 'rb') as f:
raw_data = f.read()
except tf.errors.NotFoundError:
logger.warning('Asset path %s not found', asset_path)
except tf.errors.OpError as e:
logger.warning("Couldn't read asset path: %s, OpError %s",
asset_path, e)
if raw_data is None:
return None, None
data, content_encoding = None, None
if tool == 'trace_viewer':
data = process_raw_trace(raw_data)
elif tool == 'tensorflow_stats':
if tqx == 'out:csv;':
data = tf_stats_proto_to_gviz.to_csv(raw_data)
else:
data = tf_stats_proto_to_gviz.to_json(raw_data)
elif tool == 'overview_page@':
data = overview_page_proto_to_gviz.to_json(raw_data)
elif tool == 'input_pipeline_analyzer@':
data = input_pipeline_proto_to_gviz.to_json(raw_data)
elif tool == 'kernel_stats':
if tqx == 'out:csv;':
data = kernel_stats_proto_to_gviz.to_csv(raw_data)
else:
data = kernel_stats_proto_to_gviz.to_json(raw_data)
elif tool == 'memory_profile':
logger.info('Accessing memory_profile data')
data = raw_data
content_encoding = 'gzip'
elif tool in _RAW_DATA_TOOLS:
data = raw_data
if tool[-1] == '#':
content_encoding = 'gzip'
return data, content_encoding