Update loading script

medical_dialog.py

@@ -46,15 +46,21 @@ _LICENSE = "Unknown"
 
 # URLS of processed data
 _URLS = {
-    "en": {
-        "train": "https://drive.google.com/uc?export=download&id=1ria4E6IdTIPsikL4Glm3uy1tFKJKw0W8",
-        "validation": "https://drive.google.com/uc?export=download&id=1KAZneuwdfEVQQM6euCX4pMDP-9DQpiB5",
-        "test": "https://drive.google.com/uc?export=download&id=10izqL71kcgnteYsf87Vh6j_mZ8sZM2Rc",
+    "en": "data/Medical-Dialogue-Dataset-English.zip",
+    "zh": "data/Medical-Dialogue-Dataset-Chinese.zip",
+    "processed.en": "data/processed-english.zip",
+    "processed.zh": "data/processed-chinese.zip",
+}
+_FILENAMES = {
+    "processed.en": {
+        "train": "english-train.json",
+        "validation": "english-dev.json",
+        "test": "english-test.json",
     },
-    "zh": {
-        "train": "https://drive.google.com/uc?export=download&id=1AaDJoHaiHAwEZwtskRH8oL1UP4FRgmgx",
-        "validation": "https://drive.google.com/uc?export=download&id=1TvfZCmQqP1kURIfEinOcj5VOPelTuGwI",
-        "test": "https://drive.google.com/uc?export=download&id=1pmmG95Yl6mMXRXDDSRb9-bYTxOE7ank5",
+    "processed.zh": {
+        "train": "train_data.json",
+        "validation": "validate_data.json",
+        "test": "test_data.json",
     },
 }
 
@@ -77,33 +83,6 @@ class MedicalDialog(datasets.GeneratorBasedBuilder):
         ),
     ]
 
-    @property
-    def manual_download_instructions(self):
-        *processed, _ = self.config.name.split(".")
-        return (
-            None
-            if processed
-            else """\
-    \n  For English:\nYou need to go to https://drive.google.com/drive/folders/1g29ssimdZ6JzTST6Y8g6h-ogUNReBtJD?usp=sharing,\
-    and manually download the dataset from Google Drive. Once it is completed,
-    a file named Medical-Dialogue-Dataset-English-<timestamp-info>.zip will appear in your Downloads folder(
-    or whichever folder your browser chooses to save files to). Unzip the folder to obtain
-    a folder named "Medical-Dialogue-Dataset-English" several text files.
-
-    Now, you can specify the path to this folder for the data_dir argument in the
-    datasets.load_dataset(...) option.
-    The <path/to/folder> can e.g. be "/Downloads/Medical-Dialogue-Dataset-English".
-    The data can then be loaded using the below command:\
-         `datasets.load_dataset("medical_dialog", name="en", data_dir="/Downloads/Medical-Dialogue-Dataset-English")`.
-
-    \n  For Chinese:\nFollow the above process. Change the 'name' to 'zh'.The download link is https://drive.google.com/drive/folders/1r09_i8nJ9c1nliXVGXwSqRYqklcHd9e2
-
-    **NOTE**
-    - A caution while downloading from drive. It is better to download single files since creating a zip might not include files <500 MB. This has been observed mutiple times.
-    - After downloading the files and adding them to the appropriate folder, the path of the folder can be given as input tu the data_dir path.
-    """
-        )
-
     def _info(self):
         if self.config.name == "zh":
             features = datasets.Features(
@@ -158,23 +137,13 @@ class MedicalDialog(datasets.GeneratorBasedBuilder):
         """Returns SplitGenerators."""
         *processed, lang = self.config.name.split(".")
         if processed:
-            data_dir = dl_manager.download(_URLS[lang])
+            # data_dir = dl_manager.download(_URLS[lang])
+            data_dir = dl_manager.download_and_extract(_URLS[self.config.name])
             splits = [datasets.Split.TRAIN, datasets.Split.VALIDATION, datasets.Split.TEST]
-            return [datasets.SplitGenerator(name=split, gen_kwargs={"filepaths": data_dir[split]}) for split in splits]
+            return [datasets.SplitGenerator(name=split, gen_kwargs={"filepaths": os.path.join(data_dir, _FILENAMES[self.config.name][split])}) for split in splits]
         else:
-            path_to_manual_file = os.path.abspath(os.path.expanduser(dl_manager.manual_dir))
-            if not os.path.exists(path_to_manual_file):
-                raise FileNotFoundError(
-                    f"{path_to_manual_file} does not exist. Make sure you insert a manual dir via `datasets.load_dataset('medical_dialog', data_dir=...)`. Manual download instructions: {self.manual_download_instructions})"
-                )
-
-            filepaths = [
-                os.path.join(path_to_manual_file, txt_file_name)
-                for txt_file_name in sorted(os.listdir(path_to_manual_file))
-                if txt_file_name.endswith("txt")
-            ]
-
-            return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": filepaths})]
+            archive = dl_manager.download(_URLS[self.config.name])
+            return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": dl_manager.iter_archive(archive)})]
 
     def _generate_examples(self, filepaths):
         """Yields examples. Iterates over each file and give the creates the corresponding features.
@@ -205,130 +174,130 @@ class MedicalDialog(datasets.GeneratorBasedBuilder):
                                 array = ""
         else:
             id_ = -1
-            for filepath in filepaths:
-                with open(filepath, encoding="utf-8") as f_in:
-                    # Parameters to just "sectionize" the raw data
-                    last_part = ""
-                    last_dialog = {}
-                    last_list = []
-                    last_user = ""
-                    check_list = []
-
-                    # These flags are present to have a single function address both chinese and english data
-                    # English data is a little hahazard (i.e. the sentences spans multiple different lines),
-                    # Chinese is compact with one line for doctor and patient.
-                    conv_flag = False
-                    des_flag = False
-
-                    while True:
-                        line = f_in.readline()
-                        if not line:
-                            break
+            for filepath, f_in in filepaths:
+                # with open(filepath, encoding="utf-8") as f_in:
+                # Parameters to just "sectionize" the raw data
+                last_part = ""
+                last_dialog = {}
+                last_list = []
+                last_user = ""
+                check_list = []
+
+                # These flags are present to have a single function address both chinese and english data
+                # English data is a little hahazard (i.e. the sentences spans multiple different lines),
+                # Chinese is compact with one line for doctor and patient.
+                conv_flag = False
+                des_flag = False
+
+                while True:
+                    line = f_in.readline().decode("utf-8")
+                    if not line:
+                        break
+
+                    # Extracting the dialog id
+                    if line[:2] == "id":  # Hardcode alert!
+                        # Handling ID references that may come in the description
+                        # These were observed in the Chinese dataset and were not
+                        # followed by numbers
+                        try:
+                            dialogue_id = int(re.findall(r"\d+", line)[0])
+                        except IndexError:
+                            continue
+
+                    # Extracting the url
+                    if line[:4] == "http":  # Hardcode alert!
+                        dialogue_url = line.rstrip()
+
+                    # Extracting the patient info from description.
+                    if line[:11] == "Description":  # Hardcode alert!
+                        last_part = "description"
+                        last_dialog = {}
+                        last_list = []
+                        last_user = ""
+                        last_conv = {"speaker": "", "utterance": ""}
+                        while True:
+                            line = f_in.readline().decode("utf-8")
+                            if (not line) or (line in ["\n", "\n\r"]):
+                                break
+                            else:
+                                if data_lang == "zh":  # Condition in chinese
+                                    if line[:5] == "病情描述：":  # Hardcode alert!
+                                        last_user = "病人"
+                                        sen = f_in.readline().decode("utf-8").rstrip()
+                                        des_flag = True
 
-                        # Extracting the dialog id
-                        if line[:2] == "id":  # Hardcode alert!
-                            # Handling ID references that may come in the description
-                            # These were observed in the Chinese dataset and were not
-                            # followed by numbers
-                            try:
-                                dialogue_id = int(re.findall(r"\d+", line)[0])
-                            except IndexError:
-                                continue
+                                if data_lang == "en":
+                                    last_user = "Patient"
+                                    sen = line.rstrip()
+                                    des_flag = True
+
+                                if des_flag:
+                                    if sen == "":
+                                        continue
+                                    if sen in check_list:
+                                        last_conv["speaker"] = ""
+                                        last_conv["utterance"] = ""
+                                    else:
+                                        last_conv["speaker"] = last_user
+                                        last_conv["utterance"] = sen
+                                        check_list.append(sen)
+                                    des_flag = False
+                                    break
+                    # Extracting the conversation info from dialogue.
+                    elif line[:8] == "Dialogue":  # Hardcode alert!
+                        if last_part == "description" and len(last_conv["utterance"]) > 0:
+                            last_part = "dialogue"
+                            if data_lang == "zh":
+                                last_user = "病人"
 
-                        # Extracting the url
-                        if line[:4] == "http":  # Hardcode alert!
-                            dialogue_url = line.rstrip()
+                            if data_lang == "en":
+                                last_user = "Patient"
 
-                        # Extracting the patient info from description.
-                        if line[:11] == "Description":  # Hardcode alert!
-                            last_part = "description"
-                            last_dialog = {}
-                            last_list = []
-                            last_user = ""
-                            last_conv = {"speaker": "", "utterance": ""}
                             while True:
-                                line = f_in.readline()
+                                line = f_in.readline().decode("utf-8")
                                 if (not line) or (line in ["\n", "\n\r"]):
+                                    conv_flag = False
+                                    last_user = ""
+                                    last_list.append(copy.deepcopy(last_conv))
+                                    # To ensure close of conversation, only even number of sentences
+                                    # are extracted
+                                    last_turn = len(last_list)
+                                    if int(last_turn / 2) > 0:
+                                        temp = int(last_turn / 2)
+                                        id_ += 1
+                                        last_dialog["file_name"] = filepath
+                                        last_dialog["dialogue_id"] = dialogue_id
+                                        last_dialog["dialogue_url"] = dialogue_url
+                                        last_dialog["dialogue_turns"] = last_list[: temp * 2]
+                                        yield id_, last_dialog
                                     break
-                                else:
-                                    if data_lang == "zh":  # Condition in chinese
-                                        if line[:5] == "病情描述：":  # Hardcode alert!
-                                            last_user = "病人"
-                                            sen = f_in.readline().rstrip()
-                                            des_flag = True
 
-                                    if data_lang == "en":
-                                        last_user = "Patient"
-                                        sen = line.rstrip()
-                                        des_flag = True
-
-                                    if des_flag:
-                                        if sen == "":
-                                            continue
-                                        if sen in check_list:
-                                            last_conv["speaker"] = ""
-                                            last_conv["utterance"] = ""
-                                        else:
-                                            last_conv["speaker"] = last_user
-                                            last_conv["utterance"] = sen
-                                            check_list.append(sen)
-                                        des_flag = False
-                                        break
-                        # Extracting the conversation info from dialogue.
-                        elif line[:8] == "Dialogue":  # Hardcode alert!
-                            if last_part == "description" and len(last_conv["utterance"]) > 0:
-                                last_part = "dialogue"
                                 if data_lang == "zh":
-                                    last_user = "病人"
+                                    if line[:3] == "病人：" or line[:3] == "医生：":  # Hardcode alert!
+                                        user = line[:2]  # Hardcode alert!
+                                        line = f_in.readline().decode("utf-8")
+                                        conv_flag = True
 
+                                # The elif block is to ensure that multi-line sentences are captured.
+                                # This has been observed only in english.
                                 if data_lang == "en":
-                                    last_user = "Patient"
-
-                                while True:
-                                    line = f_in.readline()
-                                    if (not line) or (line in ["\n", "\n\r"]):
-                                        conv_flag = False
-                                        last_user = ""
+                                    if line.strip() == "Patient:" or line.strip() == "Doctor:":  # Hardcode alert!
+                                        user = line.replace(":", "").rstrip()
+                                        line = f_in.readline().decode("utf-8")
+                                        conv_flag = True
+                                    elif line[:2] != "id":  # Hardcode alert!
+                                        conv_flag = True
+
+                                # Continues till the next ID is parsed
+                                if conv_flag:
+                                    sen = line.rstrip()
+                                    if sen == "":
+                                        continue
+
+                                    if user == last_user:
+                                        last_conv["utterance"] = last_conv["utterance"] + sen
+                                    else:
+                                        last_user = user
                                         last_list.append(copy.deepcopy(last_conv))
-                                        # To ensure close of conversation, only even number of sentences
-                                        # are extracted
-                                        last_turn = len(last_list)
-                                        if int(last_turn / 2) > 0:
-                                            temp = int(last_turn / 2)
-                                            id_ += 1
-                                            last_dialog["file_name"] = filepath
-                                            last_dialog["dialogue_id"] = dialogue_id
-                                            last_dialog["dialogue_url"] = dialogue_url
-                                            last_dialog["dialogue_turns"] = last_list[: temp * 2]
-                                            yield id_, last_dialog
-                                        break
-
-                                    if data_lang == "zh":
-                                        if line[:3] == "病人：" or line[:3] == "医生：":  # Hardcode alert!
-                                            user = line[:2]  # Hardcode alert!
-                                            line = f_in.readline()
-                                            conv_flag = True
-
-                                    # The elif block is to ensure that multi-line sentences are captured.
-                                    # This has been observed only in english.
-                                    if data_lang == "en":
-                                        if line.strip() == "Patient:" or line.strip() == "Doctor:":  # Hardcode alert!
-                                            user = line.replace(":", "").rstrip()
-                                            line = f_in.readline()
-                                            conv_flag = True
-                                        elif line[:2] != "id":  # Hardcode alert!
-                                            conv_flag = True
-
-                                    # Continues till the next ID is parsed
-                                    if conv_flag:
-                                        sen = line.rstrip()
-                                        if sen == "":
-                                            continue
-
-                                        if user == last_user:
-                                            last_conv["utterance"] = last_conv["utterance"] + sen
-                                        else:
-                                            last_user = user
-                                            last_list.append(copy.deepcopy(last_conv))
-                                            last_conv["utterance"] = sen
-                                            last_conv["speaker"] = user
+                                        last_conv["utterance"] = sen
+                                        last_conv["speaker"] = user