kaknikhil commented on a change in pull request #399: DL: Enable transfer
learning
URL: https://github.com/apache/madlib/pull/399#discussion_r288684869
##########
File path:
src/ports/postgres/modules/deep_learning/keras_model_arch_table.py_in
##########
@@ -53,88 +53,83 @@ class Format:
arch = plpy.execute(sql)[0]
"""
- col_names = ('model_id', 'model_arch', 'model_weights',
'__internal_madlib_id__')
- col_types = ('SERIAL PRIMARY KEY', 'JSON', 'DOUBLE PRECISION[]', 'TEXT')
- (MODEL_ID, MODEL_ARCH, MODEL_WEIGHTS, __INTERNAL_MADLIB_ID__) = col_names
-
-@MinWarning("warning")
-def _execute(sql,max_rows=0):
- return plpy.execute(sql,max_rows)
-
-def load_keras_model(schema_madlib, keras_model_arch_table,
- model_arch, **kwargs):
+ col_names = ('model_id', 'model_arch', 'model_weights', 'name',
'description',
+ '__internal_madlib_id__')
+ col_types = ('SERIAL PRIMARY KEY', 'JSON', 'bytea', 'TEXT', 'TEXT', 'TEXT')
+ (MODEL_ID, MODEL_ARCH, MODEL_WEIGHTS, NAME, DESCRIPTION,
+ __INTERNAL_MADLIB_ID__) = col_names
+
+def load_keras_model(keras_model_arch_table, model_arch, model_weights,
+ name, description, **kwargs):
model_arch_table = quote_ident(keras_model_arch_table)
if not table_exists(model_arch_table):
- col_defs = get_col_name_type_sql_string(Format.col_names,
- Format.col_types)
+ col_defs = get_col_name_type_sql_string(ModelArchSchema.col_names,
+ ModelArchSchema.col_types)
sql = "CREATE TABLE {model_arch_table} ({col_defs})" \
.format(**locals())
- _execute(sql)
+ plpy.execute(sql, 0)
plpy.info("Keras Model Arch: Created new keras model arch table {0}." \
.format(model_arch_table))
else:
missing_cols = columns_missing_from_table(model_arch_table,
- Format.col_names)
+ ModelArchSchema.col_names)
if len(missing_cols) > 0:
plpy.error("Keras Model Arch: Invalid keras model arch table {0},"
" missing columns: {1}".format(model_arch_table,
missing_cols))
unique_str = unique_string(prefix_has_temp=False)
-
- sql = """INSERT INTO {model_arch_table} ({model_arch_col},
{internal_id_col})
- VALUES({model_arch}, '{unique_str}');
- SELECT {model_id_col}, {model_arch_col}
- FROM {model_arch_table} WHERE {internal_id_col} =
'{unique_str}'
- """.format(model_arch_table=model_arch_table,
- model_arch_col=Format.MODEL_ARCH,
- unique_str=unique_str,
- model_arch=quote_literal(model_arch),
- model_id_col=Format.MODEL_ID,
- internal_id_col=Format.__INTERNAL_MADLIB_ID__)
- res = _execute(sql,1)
-
- if len(res) != 1 or res[0][Format.MODEL_ARCH] != model_arch:
+ insert_query = plpy.prepare("INSERT INTO {model_arch_table} "
+ "VALUES(DEFAULT, $1, $2, $3, $4,
$5);".format(**locals()),
+ ModelArchSchema.col_types[1:])
+ insert_res = plpy.execute(insert_query,[model_arch, model_weights, name,
description,
+ unique_str], 0)
+
+ select_query = "SELECT {model_id_col}, {model_arch_col} FROM
{model_arch_table} " \
+ "WHERE {internal_id_col} = '{unique_str}'".format(
+ model_id_col=ModelArchSchema.MODEL_ID,
+ model_arch_col=ModelArchSchema.MODEL_ARCH,
+ model_arch_table=model_arch_table,
+ internal_id_col=ModelArchSchema.__INTERNAL_MADLIB_ID__,
+ unique_str=unique_str)
+ select_res = plpy.execute(select_query,1)
+
+ if len(select_res) != 1 or select_res[0][ModelArchSchema.MODEL_ARCH] !=
model_arch:
raise Exception("Failed to insert new row in {0} table--try again?"
.format(model_arch_table))
plpy.info("Keras Model Arch: Added model id {0} to {1} table".
- format(res[0][Format.MODEL_ID], model_arch_table))
+ format(select_res[0][ModelArchSchema.MODEL_ID],
model_arch_table))
-def delete_keras_model(schema_madlib, keras_model_arch_table,
- model_id, **kwargs):
+def delete_keras_model(keras_model_arch_table, model_id, **kwargs):
model_arch_table = quote_ident(keras_model_arch_table)
input_tbl_valid(model_arch_table, "Keras Model Arch")
- missing_cols = columns_missing_from_table(model_arch_table,
Format.col_names)
+ missing_cols = columns_missing_from_table(model_arch_table,
ModelArchSchema.col_names)
if len(missing_cols) > 0:
plpy.error("Keras Model Arch: Invalid keras model arch table {0},"
" missing columns: {1}".format(model_arch_table,
missing_cols))
sql = """
DELETE FROM {model_arch_table} WHERE {model_id_col}={model_id}
- """.format(model_arch_table=model_arch_table,
model_id_col=Format.MODEL_ID,
+ """.format(model_arch_table=model_arch_table,
model_id_col=ModelArchSchema.MODEL_ID,
model_id=model_id)
- res = _execute(sql)
+ res = plpy.execute(sql, 0)
Review comment:
I believe the reason here is that we pass 0 for all the queries that don't
need to return any rows. I don't think it matters either way but I will keep
the code for now.
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
[email protected]
With regards,
Apache Git Services
