Implemented simple-view for classification and QA. Added CLI option

CHANGELOG.md

@@ -4,6 +4,10 @@ All notable changes to this project will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## UNRELEASED
+
+- Removed blank string answer in Question Answering predictions
+
 ## [0.45.2] - 2020-07-19
 
 ### Added

bin/simple-viewer

@@ -0,0 +1,14 @@
+#!/bin/bash
+cat >run_simple_transformers_streamlit_app.py <<'END_SCRIPT'
+#!/usr/bin/env python
+from simpletransformers.streamlit.simple_view import streamlit_runner
+
+
+streamlit_runner()
+
+END_SCRIPT
+
+# Run
+streamlit run run_simple_transformers_streamlit_app.py
+
+rm run_simple_transformers_streamlit_app.py

setup.py

@@ -13,6 +13,7 @@
     long_description_content_type="text/markdown",
     url="https://github.com/ThilinaRajapakse/simpletransformers/",
     packages=find_packages(),
+    scripts=["bin/simple-viewer"],
     classifiers=[
         "Intended Audience :: Science/Research",
         "License :: OSI Approved :: Apache Software License",

simpletransformers/config/model_args.py

@@ -50,6 +50,8 @@ class ModelArgs:
     manual_seed: int = None
     max_grad_norm: float = 1.0
     max_seq_length: int = 128
+    model_type: str = None
+    model_name: str = None
     multiprocessing_chunksize: int = 500
     n_gpu: int = 1
     no_cache: bool = False
@@ -104,6 +106,7 @@ class ClassificationArgs(ModelArgs):
     Model args for a ClassificationModel
     """
 
+    model_class: str = "ClassificationModel"
     labels_list: list = field(default_factory=list)
     labels_map: dict = field(default_factory=dict)
     lazy_delimiter: str = "\t"
@@ -125,6 +128,7 @@ class MultiLabelClassificationArgs(ModelArgs):
     Model args for a MultiLabelClassificationModel
     """
 
+    model_class: str = "MultiLabelClassificationModel"
     sliding_window: bool = False
     stride: float = 0.8
     threshold: float = 0.5
@@ -140,6 +144,7 @@ class NERArgs(ModelArgs):
     Model args for a NERModel
     """
 
+    model_class: str = "NERModel"
     classification_report: bool = False
     labels_list: list = field(default_factory=list)
     lazy_loading: bool = False
@@ -152,6 +157,7 @@ class QuestionAnsweringArgs(ModelArgs):
     Model args for a QuestionAnsweringModel
     """
 
+    model_class: str = "QuestionAnsweringModel"
     doc_stride: int = 384
     early_stopping_metric: str = "correct"
     early_stopping_metric_minimize: bool = False
@@ -168,6 +174,7 @@ class T5Args(ModelArgs):
     Model args for a T5Model
     """
 
+    model_class: str = "T5Model"
     dataset_class: Dataset = None
     do_sample: bool = False
     early_stopping: bool = True
@@ -190,6 +197,7 @@ class LanguageModelingArgs(ModelArgs):
     Model args for a LanguageModelingModel
     """
 
+    model_class: str = "LanguageModelingModel"
     block_size: int = -1
     config_name: str = None
     dataset_class: Dataset = None
@@ -219,6 +227,7 @@ class Seq2SeqArgs(ModelArgs):
     Model args for a Seq2SeqModel
     """
 
+    model_class: str = "Seq2SeqModel"
     base_marian_model_name: str = None
     dataset_class: Dataset = None
     do_sample: bool = False
@@ -241,6 +250,7 @@ class LanguageGenerationArgs(ModelArgs):
     Model args for a LanguageGenerationModel
     """
 
+    model_class: str = "LanguageGenerationModel"
     do_sample: bool = True
     early_stopping: bool = True
     evaluate_generated_text: bool = False
@@ -267,6 +277,7 @@ class ConvAIArgs(ModelArgs):
     Model args for a ConvAIModel
     """
 
+    model_class: str = "ConvAIModel"
     do_sample: bool = True
     lm_coef: float = 2.0
     max_history: int = 2
@@ -286,6 +297,7 @@ class MultiModalClassificationArgs(ModelArgs):
     Model args for a MultiModalClassificationModel
     """
 
+    model_class: str = "MultiModalClassificationModel"
     regression: bool = False
     num_image_embeds: int = 1
     text_label: str = "text"

simpletransformers/question_answering/question_answering_model.py

@@ -944,8 +944,8 @@ def predict(self, to_predict, n_best_size=None):
                 examples, features, all_results, n_best_size, args.max_answer_length, False, False, True, False,
             )
 
-        answer_list = [{"id": answer["id"], "answer": answer["answer"]} for answer in answers]
-        probability_list = [{"id": answer["id"], "probability": answer["probability"]} for answer in answers]
+        answer_list = [{"id": answer["id"], "answer": answer["answer"][:-1]} for answer in answers]
+        probability_list = [{"id": answer["id"], "probability": answer["probability"][:-1]} for answer in answers]
 
         return answer_list, probability_list