Merge branch 'master' into dependabot-pip-requirements-datasets-gte-2…

….0.0-and-lte-2.14.3

CHANGELOG.md

@@ -8,6 +8,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Added
 
+-
 
 
 ### Changed
@@ -17,7 +18,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Fixed
 
-
+- Fixed `_strip` for eventually `int` ([#1667](https://github.com/Lightning-AI/lightning-flash/pull/1667))
+- Fixed checking `target_formatter` as attrib type ([#1665](https://github.com/Lightning-AI/lightning-flash/pull/1665))
+- Fixed remote check in `download_data` ([#1666](https://github.com/Lightning-AI/lightning-flash/pull/1666))
 
 
 ## [0.8.2] - 2023-06-30

requirements/datatype_image.txt

@@ -1,7 +1,7 @@
 # NOTE: all pins for latest are for CI consistency unless it is `strict`, then it is also forced in setup
 
 torchvision <=0.15.2
-timm >0.4.5, <=0.9.2  # effdet 0.3.0 depends on timm>=0.4.12
+timm >0.4.5, <=0.9.5  # effdet 0.3.0 depends on timm>=0.4.12
 lightning-bolts >=0.7.0, <0.8.0
 Pillow >8.0, <=10.0.0
 albumentations >1.0.0, <=1.3.1

requirements/serve.txt

@@ -6,8 +6,8 @@ cytoolz >0.11, <=0.12.2
 graphviz >=0.19, <=0.20.1
 tqdm >4.60, <=4.65.0
 fastapi >0.65, <=0.100.0
-pydantic >1.8.1, <=2.0.3
-starlette <=0.30.0
+pydantic >1.8.1, <=2.1.1
+starlette <=0.31.0
 uvicorn[standard] >=0.12.0, <=0.23.2
 aiofiles >22.1.0, <=23.1.0
 jinja2 >=3.0.0, <3.2.0

requirements/testing_audio.txt

@@ -3,7 +3,7 @@ torch ==2.0.1
 torchaudio ==2.0.2
 torchvision ==0.15.2
 
-timm >0.4.5, <=0.9.2  # effdet 0.3.0 depends on timm>=0.4.12
+timm >0.4.5, <=0.9.5  # effdet 0.3.0 depends on timm>=0.4.12
 lightning-bolts >=0.7.0, <0.8.0
 Pillow >8.0, <=10.0.0
 albumentations >1.0.0, <=1.3.1

src/flash/audio/classification/input.py

@@ -138,6 +138,7 @@ def load_data(
         # If we had binary multi-class targets then we also know the labels (column names)
         if (
             self.training
+            and hasattr(self, "target_formatter")
             and isinstance(self.target_formatter, MultiBinaryTargetFormatter)
             and isinstance(target_keys, List)
         ):

src/flash/core/data/utilities/classification.py

@@ -42,8 +42,11 @@ def _as_list(x: Union[List, Tensor, np.ndarray]) -> List:
     return x
 
 
-def _strip(x: str) -> str:
-    return x.strip(", ")
+def _strip(x: Union[str, int]) -> str:
+    """Replace both ` ` and `,` from str."""
+    if isinstance(x, str):
+        return x.strip(", ")
+    return str(x)
 
 
 @dataclass

src/flash/core/data/utils.py

@@ -59,7 +59,7 @@
 }
 
 
-def download_data(url: str, path: str = "data/", verbose: bool = False) -> None:
+def download_data(url: str, path: str = "data/", verbose: bool = False, chunk_size: int = 1024) -> None:
     """Download file with progressbar.
 
     # Code adapted from: https://gist.github.com/ruxi/5d6803c116ec1130d484a4ab8c00c603
@@ -78,39 +78,42 @@ def download_data(url: str, path: str = "data/", verbose: bool = False) -> None:
         [...]
 
     """
+    local_filename = os.path.join(path, url.split("/")[-1])
+    if os.path.exists(local_filename):
+        if verbose:
+            print(f"local file already exists: '{local_filename}'")
+        return
+
+    os.makedirs(path, exist_ok=True)
     # Disable warning about making an insecure request
     urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
 
-    if not os.path.exists(path):
-        os.makedirs(path)
-    local_filename = os.path.join(path, url.split("/")[-1])
     r = requests.get(url, stream=True, verify=False)
     file_size = int(r.headers["Content-Length"]) if "Content-Length" in r.headers else 0
-    chunk_size = 1024
     num_bars = int(file_size / chunk_size)
     if verbose:
-        print({"file_size": file_size})
-        print({"num_bars": num_bars})
-
-    if not os.path.exists(local_filename):
-        with open(local_filename, "wb") as fp:
-            for chunk in tq(
-                r.iter_content(chunk_size=chunk_size),
-                total=num_bars,
-                unit="KB",
-                desc=local_filename,
-                leave=True,  # progressbar stays
-            ):
-                fp.write(chunk)  # type: ignore
-
-    def extract_tarfile(file_path: str, extract_path: str, mode: str):
-        if os.path.exists(file_path):
-            with tarfile.open(file_path, mode=mode) as tar_ref:
-                for member in tar_ref.getmembers():
-                    try:
-                        tar_ref.extract(member, path=extract_path, set_attrs=False)
-                    except PermissionError:
-                        raise PermissionError(f"Could not extract tar file {file_path}")
+        print(f"file size: {file_size}")
+        print(f"num bars: {num_bars}")
+
+    with open(local_filename, "wb") as fp:
+        for chunk in tq(
+            r.iter_content(chunk_size=chunk_size),
+            total=num_bars,
+            unit="KB",
+            desc=local_filename,
+            leave=True,  # progressbar stays
+        ):
+            fp.write(chunk)  # type: ignore
+
+    def extract_tarfile(file_path: str, extract_path: str, mode: str) -> None:
+        if not os.path.exists(file_path):
+            return
+        with tarfile.open(file_path, mode=mode) as tar_ref:
+            for member in tar_ref.getmembers():
+                try:
+                    tar_ref.extract(member, path=extract_path, set_attrs=False)
+                except PermissionError:
+                    raise PermissionError(f"Could not extract tar file {file_path}")
 
     if ".zip" in local_filename:
         if os.path.exists(local_filename):

src/flash/image/classification/input.py

@@ -157,6 +157,7 @@ def load_data(
         # If we had binary multi-class targets then we also know the labels (column names)
         if (
             self.training
+            and hasattr(self, "target_formatter")
             and isinstance(self.target_formatter, MultiBinaryTargetFormatter)
             and isinstance(target_keys, List)
         ):

src/flash/text/classification/input.py

@@ -53,7 +53,11 @@ def load_data(
             self.load_target_metadata(targets, target_formatter=target_formatter)
 
             # If we had binary multi-class targets then we also know the labels (column names)
-            if isinstance(self.target_formatter, MultiBinaryTargetFormatter) and isinstance(target_keys, List):
+            if (
+                hasattr(self, "target_formatter")
+                and isinstance(self.target_formatter, MultiBinaryTargetFormatter)
+                and isinstance(target_keys, List)
+            ):
                 self.labels = target_keys
 
         # remove extra columns

src/flash/video/classification/input.py

@@ -215,6 +215,7 @@ def load_data(
         # If we had binary multi-class targets then we also know the labels (column names)
         if (
             self.training
+            and hasattr(self, "target_formatter")
             and isinstance(self.target_formatter, MultiBinaryTargetFormatter)
             and isinstance(target_keys, List)
         ):
@@ -243,6 +244,7 @@ def load_data(
         # If we had binary multi-class targets then we also know the labels (column names)
         if (
             self.training
+            and hasattr(self, "target_formatter")
             and isinstance(self.target_formatter, MultiBinaryTargetFormatter)
             and isinstance(targets, List)
         ):