kaknikhil commented on a change in pull request #360: Deep Learning: Add
support for one-hot encoded dep var
URL: https://github.com/apache/madlib/pull/360#discussion_r270537028
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File path: src/ports/postgres/modules/deep_learning/madlib_keras_helper.py_in
##########
@@ -174,21 +182,129 @@ def get_data_as_np_array(table_name, y, x, input_shape,
num_classes):
indep_len = len(val_data[0][x])
pixels_per_image = int(input_shape[0] * input_shape[1] * input_shape[2])
x_validation = np.ndarray((0,indep_len, pixels_per_image))
- y_validation = np.ndarray((0,indep_len))
+ y_validation = np.ndarray((0,indep_len, num_classes))
for i in range(len(val_data)):
x_test = np.asarray((val_data[i][x],))
x_test = x_test.reshape(1, indep_len, pixels_per_image)
y_test = np.asarray((val_data[i][y],))
- y_test = y_test.reshape(1, indep_len)
x_validation=np.concatenate((x_validation, x_test))
y_validation=np.concatenate((y_validation, y_test))
num_test_examples = x_validation.shape[0]
x_validation = x_validation.reshape(indep_len * num_test_examples,
*input_shape)
x_validation = x_validation.astype('float64')
- y_validation = y_validation.reshape(indep_len * num_test_examples)
-
- x_validation = x_validation.astype('float64')
- #x_validation /= 255.0
- y_validation = keras_utils.to_categorical(y_validation, num_classes)
+ y_validation = y_validation.reshape(indep_len * num_test_examples,
num_classes)
return x_validation, y_validation
+
+CLASS_VALUES_COLNAME = "class_values"
+class FitInputValidator:
+ def __init__(self, source_table, validation_table, output_model_table,
+ model_arch_table, dependent_varname, independent_varname,
+ num_iterations):
+ self.source_table = source_table
+ self.validation_table = validation_table
+ self.output_model_table = output_model_table
+ self.model_arch_table = model_arch_table
+ self.dependent_varname = dependent_varname
+ self.independent_varname = independent_varname
+ self.num_iterations = num_iterations
+ self.source_summary_table = None
+ if self.source_table:
+ self.source_summary_table = add_postfix(
+ self.source_table, "_summary")
+ if self.output_model_table:
+ self.output_summary_model_table = add_postfix(
+ self.output_model_table, "_summary")
+ self.class_values_colname = CLASS_VALUES_COLNAME
Review comment:
Why do we need a variable for this ? Why can't we just use
`CLASS_VALUES_COLNAME`
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