njayaram2 commented on a change in pull request #395: DL:
madlib_keras_evaluate() function
URL: https://github.com/apache/madlib/pull/395#discussion_r289132782
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File path: src/ports/postgres/modules/deep_learning/madlib_keras.py_in
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@@ -546,44 +531,75 @@ def fit_final(state, **kwargs):
return madlib_keras_serializer.serialize_weights_merge(
image_count, weights)
-def evaluate1(schema_madlib, model_table, test_table, id_col, model_arch_table,
- model_arch_id, dependent_varname, independent_varname,
- compile_params, output_table, **kwargs):
- # module_name = 'madlib_keras_evaluate'
- # input_tbl_valid(test_table, module_name)
- # input_tbl_valid(model_arch_table, module_name)
- # output_tbl_valid(output_table, module_name)
+def get_segments_and_gpus(gpus_per_host):
+ gpus_per_host = 0 if gpus_per_host is None else gpus_per_host
+ segments_per_host = get_segments_per_host()
- # _validate_input_args(test_table, model_arch_table, output_table)
+ if 0 < gpus_per_host < segments_per_host:
+ plpy.warning('The number of gpus per host is less than the number of '
+ 'segments per host. The support for this case is '
+ 'experimental and it may fail.')
- model_data_query = "SELECT model_data from {0}".format(model_table)
- model_data = plpy.execute(model_data_query)[0]['model_data']
+ return segments_per_host, gpus_per_host
- model_arch_query = "SELECT model_arch, model_weights FROM {0} " \
- "WHERE id = {1}".format(model_arch_table, model_arch_id)
- query_result = plpy.execute(model_arch_query)
- if not query_result or len(query_result) == 0:
- plpy.error("no model arch found in table {0} with id {1}".format(
- model_arch_table, model_arch_id))
- query_result = query_result[0]
- model_arch = query_result[Format.MODEL_ARCH]
+def evaluate(schema_madlib, model_table, test_table, output_table,
gpus_per_host, **kwargs):
+ module_name = 'madlib_keras_evaluate'
+ input_validator = EvaluateInputValidator(test_table, model_table,
output_table, module_name)
+
+ model_summary_table = input_validator.model_summary_table
+ test_summary_table = input_validator.test_summary_table
+
+ segments_per_host, gpus_per_host = get_segments_and_gpus(gpus_per_host)
+
+ model_data_query = "SELECT model_data, model_arch from
{0}".format(model_table)
+ res = plpy.execute(model_data_query)[0]
+ model_data = res['model_data']
+ model_arch = res['model_arch']
+
+ input_shape = get_input_shape(model_arch)
+ input_validator.validate_input_shape(input_shape)
+
+ compile_params_query = "SELECT compile_params, metrics_type FROM
{0}".format(model_summary_table)
+ res = plpy.execute(compile_params_query)[0]
+ metrics_type = res['metrics_type']
+ compile_params = res['compile_params']
compile_params = "$madlib$" + compile_params + "$madlib$"
Review comment:
We can combine the two lines related to `compile_params` into one.
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