no-op

PiperOrigin-RevId: 654183491

tfx/orchestration/experimental/core/pipeline_ir_codec.py

@@ -0,0 +1,110 @@
+# Copyright 2024 Google LLC. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""A class for encoding / decoding pipeline IR."""
+
+import base64
+import json
+import os
+import threading
+import uuid
+
+from tfx.dsl.io import fileio
+from tfx.orchestration.experimental.core import env
+from tfx.orchestration.experimental.core import task as task_lib
+from tfx.proto.orchestration import pipeline_pb2
+
+from google.protobuf import message
+
+
+class PipelineIRCodec:
+  """A class for encoding / decoding pipeline IR."""
+
+  _ORCHESTRATOR_METADATA_DIR = '.orchestrator'
+  _PIPELINE_IRS_DIR = 'pipeline_irs'
+  _PIPELINE_IR_URL_KEY = 'pipeline_ir_url'
+  _obj = None
+  _lock = threading.Lock()
+
+  @classmethod
+  def get(cls) -> 'PipelineIRCodec':
+    with cls._lock:
+      if not cls._obj:
+        cls._obj = cls()
+      return cls._obj
+
+  @classmethod
+  def testonly_reset(cls) -> None:
+    """Reset global state, for tests only."""
+    with cls._lock:
+      cls._obj = None
+
+  def encode(self, pipeline: pipeline_pb2.Pipeline) -> str:
+    """Encodes pipeline IR."""
+    # Attempt to store as a base64 encoded string. If base_dir is provided
+    # and the length is too large, store the IR on disk and retain the URL.
+    # TODO(b/248786921): Always store pipeline IR to base_dir once the
+    # accessibility issue is resolved.
+
+    # Note that this setup means that every *subpipeline* will have its own
+    # "irs" dir. This is fine, though ideally we would put all pipeline IRs
+    # under the root pipeline dir, which would require us to *also* store the
+    # root pipeline dir in the IR.
+
+    base_dir = pipeline.runtime_spec.pipeline_root.field_value.string_value
+    if base_dir:
+      pipeline_ir_dir = os.path.join(
+          base_dir, self._ORCHESTRATOR_METADATA_DIR, self._PIPELINE_IRS_DIR
+      )
+      fileio.makedirs(pipeline_ir_dir)
+    else:
+      pipeline_ir_dir = None
+    pipeline_encoded = _base64_encode(pipeline)
+    max_mlmd_str_value_len = env.get_env().max_mlmd_str_value_length()
+    if (
+        base_dir
+        and pipeline_ir_dir
+        and max_mlmd_str_value_len is not None
+        and len(pipeline_encoded) > max_mlmd_str_value_len
+    ):
+      pipeline_id = task_lib.PipelineUid.from_pipeline(pipeline).pipeline_id
+      pipeline_url = os.path.join(
+          pipeline_ir_dir, f'{pipeline_id}_{uuid.uuid4()}.pb'
+      )
+      with fileio.open(pipeline_url, 'wb') as file:
+        file.write(pipeline.SerializeToString())
+      pipeline_encoded = json.dumps({self._PIPELINE_IR_URL_KEY: pipeline_url})
+    return pipeline_encoded
+
+  def decode(self, value: str) -> pipeline_pb2.Pipeline:
+    """Decodes pipeline IR."""
+    # Attempt to load as JSON. If it fails, fallback to decoding it as a base64
+    # encoded string for backward compatibility.
+    try:
+      pipeline_encoded = json.loads(value)
+      with fileio.open(
+          pipeline_encoded[self._PIPELINE_IR_URL_KEY], 'rb'
+      ) as file:
+        return pipeline_pb2.Pipeline.FromString(file.read())
+    except json.JSONDecodeError:
+      return _base64_decode_pipeline(value)
+
+
+def _base64_encode(msg: message.Message) -> str:
+  return base64.b64encode(msg.SerializeToString()).decode('utf-8')
+
+
+def _base64_decode_pipeline(pipeline_encoded: str) -> pipeline_pb2.Pipeline:
+  result = pipeline_pb2.Pipeline()
+  result.ParseFromString(base64.b64decode(pipeline_encoded))
+  return result

tfx/orchestration/experimental/core/pipeline_ir_codec_test.py

@@ -0,0 +1,128 @@
+# Copyright 2024 Google LLC. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""Tests for tfx.orchestration.experimental.core.pipeline_ir_codec."""
+import json
+import os
+from typing import List, Optional
+import tensorflow as tf
+from tfx.orchestration.experimental.core import env
+from tfx.orchestration.experimental.core import pipeline_ir_codec
+from tfx.orchestration.experimental.core import test_utils
+from tfx.proto.orchestration import pipeline_pb2
+
+
+def _test_pipeline(
+    pipeline_id,
+    execution_mode: pipeline_pb2.Pipeline.ExecutionMode = (
+        pipeline_pb2.Pipeline.ASYNC
+    ),
+    param=1,
+    pipeline_nodes: Optional[List[str]] = None,
+    pipeline_run_id: str = 'run0',
+    pipeline_root: str = '',
+):
+  pipeline = pipeline_pb2.Pipeline()
+  pipeline.pipeline_info.id = pipeline_id
+  pipeline.execution_mode = execution_mode
+  if pipeline_nodes:
+    for node in pipeline_nodes:
+      pipeline.nodes.add().pipeline_node.node_info.id = node
+    pipeline.nodes[0].pipeline_node.parameters.parameters[
+        'param'
+    ].field_value.int_value = param
+  if execution_mode == pipeline_pb2.Pipeline.SYNC:
+    pipeline.runtime_spec.pipeline_run_id.field_value.string_value = (
+        pipeline_run_id
+    )
+  pipeline.runtime_spec.pipeline_root.field_value.string_value = pipeline_root
+  return pipeline
+
+
+class TestEnv(env._DefaultEnv):
+
+  def __init__(self, base_dir, max_str_len):
+    self.base_dir = base_dir
+    self.max_str_len = max_str_len
+
+  def get_base_dir(self):
+    return self.base_dir
+
+  def max_mlmd_str_value_length(self):
+    return self.max_str_len
+
+
+class PipelineIRCodecTest(test_utils.TfxTest):
+
+  def setUp(self):
+    super().setUp()
+    self._pipeline_root = os.path.join(
+        os.environ.get('TEST_UNDECLARED_OUTPUTS_DIR', self.get_temp_dir()),
+        self.id(),
+    )
+
+  def test_encode_decode_no_base_dir(self):
+    with TestEnv(None, None):
+      pipeline = _test_pipeline('pipeline1', pipeline_nodes=['Trainer'])
+      pipeline_encoded = pipeline_ir_codec.PipelineIRCodec.get().encode(
+          pipeline
+      )
+    self.assertProtoEquals(
+        pipeline,
+        pipeline_ir_codec._base64_decode_pipeline(pipeline_encoded),
+        'Expected pipeline IR to be base64 encoded.',
+    )
+    self.assertProtoEquals(
+        pipeline,
+        pipeline_ir_codec.PipelineIRCodec.get().decode(pipeline_encoded),
+    )
+
+  def test_encode_decode_with_base_dir(self):
+    with TestEnv(self._pipeline_root, None):
+      pipeline = _test_pipeline('pipeline1', pipeline_nodes=['Trainer'])
+      pipeline_encoded = pipeline_ir_codec.PipelineIRCodec.get().encode(
+          pipeline
+      )
+    self.assertProtoEquals(
+        pipeline,
+        pipeline_ir_codec._base64_decode_pipeline(pipeline_encoded),
+        'Expected pipeline IR to be base64 encoded.',
+    )
+    self.assertProtoEquals(
+        pipeline,
+        pipeline_ir_codec.PipelineIRCodec.get().decode(pipeline_encoded),
+    )
+
+  def test_encode_decode_exceeds_max_len(self):
+    with TestEnv(self._pipeline_root, 0):
+      pipeline = _test_pipeline(
+          'pipeline1',
+          pipeline_nodes=['Trainer'],
+          pipeline_root=self.create_tempdir().full_path,
+      )
+      pipeline_encoded = pipeline_ir_codec.PipelineIRCodec.get().encode(
+          pipeline
+      )
+    self.assertProtoEquals(
+        pipeline,
+        pipeline_ir_codec.PipelineIRCodec.get().decode(pipeline_encoded),
+    )
+    self.assertEqual(
+        pipeline_ir_codec.PipelineIRCodec._PIPELINE_IR_URL_KEY,
+        next(iter(json.loads(pipeline_encoded).keys())),
+        'Expected pipeline IR URL to be stored as json.',
+    )
+
+
+if __name__ == '__main__':
+  tf.test.main()

tfx/orchestration/experimental/core/pipeline_state.py

@@ -18,8 +18,6 @@
 import copy
 import dataclasses
 import functools
-import json
-import os
 import threading
 import time
 from typing import Any, Callable, Dict, Iterator, List, Mapping, Optional, Set, Tuple, cast
@@ -28,14 +26,14 @@
 from absl import logging
 import attr
 from tfx import types
-from tfx.dsl.io import fileio
 from tfx.orchestration import data_types_utils
 from tfx.orchestration import metadata
 from tfx.orchestration import node_proto_view
 from tfx.orchestration.experimental.core import env
 from tfx.orchestration.experimental.core import event_observer
 from tfx.orchestration.experimental.core import mlmd_state
 from tfx.orchestration.experimental.core import orchestration_options
+from tfx.orchestration.experimental.core import pipeline_ir_codec
 from tfx.utils import metrics_utils
 from tfx.orchestration.experimental.core import task as task_lib
 from tfx.orchestration.experimental.core import task_gen_utils
@@ -402,77 +400,6 @@ def last_state_change_time_secs() -> float:
     return _last_state_change_time_secs
 
 
-class _PipelineIRCodec:
-  """A class for encoding / decoding pipeline IR."""
-
-  _ORCHESTRATOR_METADATA_DIR = '.orchestrator'
-  _PIPELINE_IRS_DIR = 'pipeline_irs'
-  _PIPELINE_IR_URL_KEY = 'pipeline_ir_url'
-  _obj = None
-  _lock = threading.Lock()
-
-  @classmethod
-  def get(cls) -> '_PipelineIRCodec':
-    with cls._lock:
-      if not cls._obj:
-        cls._obj = cls()
-      return cls._obj
-
-  @classmethod
-  def testonly_reset(cls) -> None:
-    """Reset global state, for tests only."""
-    with cls._lock:
-      cls._obj = None
-
-  def encode(self, pipeline: pipeline_pb2.Pipeline) -> str:
-    """Encodes pipeline IR."""
-    # Attempt to store as a base64 encoded string. If base_dir is provided
-    # and the length is too large, store the IR on disk and retain the URL.
-    # TODO(b/248786921): Always store pipeline IR to base_dir once the
-    # accessibility issue is resolved.
-
-    # Note that this setup means that every *subpipeline* will have its own
-    # "irs" dir. This is fine, though ideally we would put all pipeline IRs
-    # under the root pipeline dir, which would require us to *also* store the
-    # root pipeline dir in the IR.
-
-    base_dir = pipeline.runtime_spec.pipeline_root.field_value.string_value
-    if base_dir:
-      pipeline_ir_dir = os.path.join(
-          base_dir, self._ORCHESTRATOR_METADATA_DIR, self._PIPELINE_IRS_DIR
-      )
-      fileio.makedirs(pipeline_ir_dir)
-    else:
-      pipeline_ir_dir = None
-    pipeline_encoded = _base64_encode(pipeline)
-    max_mlmd_str_value_len = env.get_env().max_mlmd_str_value_length()
-    if (
-        base_dir
-        and pipeline_ir_dir
-        and max_mlmd_str_value_len is not None
-        and len(pipeline_encoded) > max_mlmd_str_value_len
-    ):
-      pipeline_id = task_lib.PipelineUid.from_pipeline(pipeline).pipeline_id
-      pipeline_url = os.path.join(
-          pipeline_ir_dir, f'{pipeline_id}_{uuid.uuid4()}.pb'
-      )
-      with fileio.open(pipeline_url, 'wb') as file:
-        file.write(pipeline.SerializeToString())
-      pipeline_encoded = json.dumps({self._PIPELINE_IR_URL_KEY: pipeline_url})
-    return pipeline_encoded
-
-  def decode(self, value: str) -> pipeline_pb2.Pipeline:
-    """Decodes pipeline IR."""
-    # Attempt to load as JSON. If it fails, fallback to decoding it as a base64
-    # encoded string for backward compatibility.
-    try:
-      pipeline_encoded = json.loads(value)
-      with fileio.open(pipeline_encoded[self._PIPELINE_IR_URL_KEY],
-                       'rb') as file:
-        return pipeline_pb2.Pipeline.FromString(file.read())
-    except json.JSONDecodeError:
-      return _base64_decode_pipeline(value)
-
 # Signal to record whether there are active pipelines, this is an optimization
 # to avoid generating too many RPC calls getting contexts/executions during
 # idle time. Everytime when the pipeline state is updated to active (eg. start,
@@ -668,7 +595,7 @@ def new(
       raise ValueError('Expected pipeline execution mode to be SYNC or ASYNC')
 
     exec_properties = {
-        _PIPELINE_IR: _PipelineIRCodec.get().encode(pipeline),
+        _PIPELINE_IR: pipeline_ir_codec.PipelineIRCodec.get().encode(pipeline),
         _PIPELINE_EXEC_MODE: pipeline_exec_mode,
     }
     pipeline_run_metadata_json = None
@@ -999,7 +926,7 @@ def _structure(
     env.get_env().prepare_orchestrator_for_pipeline_run(updated_pipeline)
     data_types_utils.set_metadata_value(
         self.execution.custom_properties[_UPDATED_PIPELINE_IR],
-        _PipelineIRCodec.get().encode(updated_pipeline),
+        pipeline_ir_codec.PipelineIRCodec.get().encode(updated_pipeline),
     )
     data_types_utils.set_metadata_value(
         self.execution.custom_properties[_UPDATE_OPTIONS],
@@ -1038,7 +965,9 @@ def apply_pipeline_update(self) -> None:
     )
     del self.execution.custom_properties[_UPDATED_PIPELINE_IR]
     del self.execution.custom_properties[_UPDATE_OPTIONS]
-    self.pipeline = _PipelineIRCodec.get().decode(updated_pipeline_ir)
+    self.pipeline = pipeline_ir_codec.PipelineIRCodec.get().decode(
+        updated_pipeline_ir
+    )
 
   def is_stop_initiated(self) -> bool:
     self._check_context()
@@ -1550,7 +1479,7 @@ def _get_pipeline_from_orchestrator_execution(
     execution: metadata_store_pb2.Execution) -> pipeline_pb2.Pipeline:
   pipeline_ir = data_types_utils.get_metadata_value(
       execution.properties[_PIPELINE_IR])
-  return _PipelineIRCodec.get().decode(pipeline_ir)
+  return pipeline_ir_codec.PipelineIRCodec.get().decode(pipeline_ir)
 
 
 def _get_orchestrator_context(mlmd_handle: metadata.Metadata, pipeline_id: str,
@@ -1569,12 +1498,6 @@ def _base64_encode(msg: message.Message) -> str:
   return base64.b64encode(msg.SerializeToString()).decode('utf-8')
 
 
-def _base64_decode_pipeline(pipeline_encoded: str) -> pipeline_pb2.Pipeline:
-  result = pipeline_pb2.Pipeline()
-  result.ParseFromString(base64.b64decode(pipeline_encoded))
-  return result
-
-
 def _base64_decode_update_options(
     update_options_encoded: str) -> pipeline_pb2.UpdateOptions:
   result = pipeline_pb2.UpdateOptions()