Project import generated by Copybara. (#12)

GitOrigin-RevId: c940ae2b6eabf1ea03ae27ac404d5004a4e894cc

Co-authored-by: Snowflake Authors <[email protected]>

ci/conda_recipe/meta.yaml

@@ -5,7 +5,7 @@
 
 package:
   name: snowflake-ml-python
-  version: 0.2.4 # this has to be in sync with snowflake/ml/BUILD.bazel and snowflake/ml/version.py
+  version: 0.3.0 # this has to be in sync with snowflake/ml/BUILD.bazel and snowflake/ml/version.py
 
 source:
   path: ../../
@@ -40,11 +40,11 @@ requirements:
 about:
   home: https://github.com/snowflakedb/snowflake-ml-python
   license: Apache-2.0
-  license_family : Apache
+  license_family: Apache
   license_file: ../../LICENSE.txt
   summary: Snowflake ML Library
   description: |
-      Snowflake ML client Library is used for interacting with Snowflake to build machine learning solutions.
-      Functionalities include feature engineering, modeling, model management, deployment, etc
+    Snowflake ML client Library is used for interacting with Snowflake to build machine learning solutions.
+    Functionalities include feature engineering, modeling, model management, deployment, etc
   dev_url: https://github.com/snowflakedb/snowflake-ml-python
   doc_url: https://github.com/snowflakedb/snowflake-ml-python/blob/main/README.md

snowflake/ml/BUILD.bazel

@@ -46,9 +46,9 @@ snowml_wheel(
         # versions in the requirements file, we are pinning the versions here.
         "scikit-learn==1.2.1",
         "xgboost==1.7.3",
-        "joblib>=1.0.0,<=1.1.1", # All the release versions between 1.0.0 and 1.1.1 are available in SF Conda channel.
+        "joblib>=1.0.0,<=1.1.1",  # All the release versions between 1.0.0 and 1.1.1 are available in SF Conda channel.
     ],
-    version = "0.2.4", # this has to be in sync with version.py and ci/conda_recipe/meta.yaml
+    version = "0.3.0",  # this has to be in sync with version.py and ci/conda_recipe/meta.yaml
     deps = [
         "//snowflake/ml/metrics:metrics_pkg",
         "//snowflake/ml/preprocessing:preprocessing_pkg",

snowflake/ml/_internal/BUILD.bazel

@@ -27,6 +27,7 @@ py_library(
 py_test(
     name = "file_utils_test",
     srcs = ["file_utils_test.py"],
+    timeout = "short",
     deps = [
         ":file_utils",
     ],

snowflake/ml/_internal/file_utils.py

@@ -70,10 +70,11 @@ def zip_file_or_directory_to_stream(
     with io.BytesIO() as input_stream:
         with zipfile.ZipFile(input_stream, mode="w", compression=zipfile.ZIP_DEFLATED) as zf:
 
-            cur_path = os.path.dirname(path)
-            while os.path.realpath(cur_path) != os.path.realpath(start_path):
-                zf.writestr(f"{os.path.relpath(cur_path, start_path)}/", "")
-                cur_path = os.path.dirname(cur_path)
+            if os.path.realpath(path) != os.path.realpath(start_path):
+                cur_path = os.path.dirname(path)
+                while os.path.realpath(cur_path) != os.path.realpath(start_path):
+                    zf.writestr(f"{os.path.relpath(cur_path, start_path)}/", "")
+                    cur_path = os.path.dirname(cur_path)
 
             if os.path.isdir(path):
                 for dirname, _, files in os.walk(path):

snowflake/ml/_internal/file_utils_test.py

@@ -46,3 +46,7 @@ def test_zip_file_or_directory_to_stream(self) -> None:
             importlib.import_module("snowflake.snowpark.fake_module.p")
 
             sys.path.remove(os.path.abspath(zip_module_filename))
+
+            with file_utils.zip_file_or_directory_to_stream(fake_mod_dirpath, fake_mod_dirpath) as input_stream:
+                with open(zip_module_filename, "wb") as f:
+                    f.write(input_stream.getbuffer())

snowflake/ml/registry/BUILD.bazel

@@ -11,6 +11,7 @@ py_library(
         "//snowflake/ml/_internal/utils:formatting",
         "//snowflake/ml/_internal/utils:query_result_checker",
         "//snowflake/ml/_internal/utils:uri",
+        "//snowflake/ml/_internal:file_utils",
         "//snowflake/ml/model:_model",
         "//snowflake/ml/model:_deployer",
         "//snowflake/ml/utils:telemetry",

snowflake/ml/registry/model_registry.py

@@ -12,6 +12,7 @@
 from absl import logging
 
 from snowflake import connector, snowpark
+from snowflake.ml._internal import file_utils
 from snowflake.ml._internal.utils import formatting, query_result_checker, uri
 from snowflake.ml.model import (
     _deployer,
@@ -21,7 +22,6 @@
 )
 from snowflake.ml.registry import _schema
 from snowflake.ml.utils import telemetry
-from snowflake.snowpark._internal import utils
 
 if TYPE_CHECKING:
     import pandas as pd
@@ -998,6 +998,9 @@ def log_model(
                 output, which could be inferred by calling `infer_signature` method with sample input data.
             sample_input_data: Sample of the input data for the model.
 
+        Raises:
+            TypeError: Raised when both signatures and sample_input_data is not presented. Will be captured locally.
+
         Returns:
             String of the auto-generate unique model identifier. None if failed.
         """
@@ -1031,6 +1034,8 @@ def log_model(
                         pip_requirements=pip_requirements,
                         sample_input=sample_input_data,
                     )
+                else:
+                    raise TypeError("Either signature or sample input data should exist for native model packaging.")
                 id = self.log_model_path(
                     path=tmpdir,
                     type="snowflake_native",
@@ -1174,7 +1179,6 @@ def log_model_path(
         Returns:
             String of the auto-generate unique model identifier.
         """
-
         # Copy model from local disk to remote stage.
         fully_qualified_model_stage_name = self._prepare_model_stage(model_name=name, model_version=version)
 
@@ -1183,7 +1187,7 @@ def log_model_path(
         if os.path.isfile(path):
             self._session.file.put(path, f"{fully_qualified_model_stage_name}/data")
         elif os.path.isdir(path):
-            with utils.zip_file_or_directory_to_stream(path, path, add_init_py=True) as input_stream:
+            with file_utils.zip_file_or_directory_to_stream(path, path) as input_stream:
                 self._session._conn.upload_stream(
                     input_stream=input_stream,
                     stage_location=fully_qualified_model_stage_name,

snowflake/ml/version.py

@@ -1,6 +1,6 @@
 # Update this for the versions
 # Don't change the forth version number from None
-VERSION = (0, 2, 4, None)  # this has to be in sync with BUILD.bazel and ci/conda_recipe/meta.yaml
+VERSION = (0, 3, 0, None)  # this has to be in sync with BUILD.bazel and ci/conda_recipe/meta.yaml
 
 
 def get_version() -> str: