loading script

data/X_test.npy

@@ -1,3 +1,3 @@
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+oid sha256:db29da2911cdfb2d7a340f4a4fc2481d83009febe3f85e237834ef2128957d9e
 size 10530128

data/X_train.npy

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:02f219a508b46839eb83cd34a12dc5952597550e1d83c911af7c6d59b9877278
+oid sha256:66a783a2c69d9652f40a267542cab15f33eea0da70264ad098a012ba12e0993d
 size 63180128

data/y_test.npy

@@ -1,3 +1,3 @@
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-oid sha256:996074233ccae69ee65b8551233f608adc1bce84b6b440e3531478a847958149
-size 80128
+oid sha256:ff7e84b144c037e7215dfa787d6773550c5db83029d9a4e7bae6e90f605f081d
+size 10128

data/y_train.npy

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:10226b938104d9231ead4e9a0627f17e66cd18baf31a28784f1b72147057decf
-size 480128
+oid sha256:5dd4d822cab3e20099239bc9d433d587ae3ce00e084d191079dd30b38380b336
+size 60128

dataset_infos.json

@@ -0,0 +1,64 @@
+{
+    "point-cloud-mnist": {
+        "description": "",
+        "citation": "",
+        "homepage": "",
+        "license": "",
+        "features": {
+            "image": {
+                "shape": [
+                    351,
+                    3
+                ],
+                "dtype": "uint8",
+                "id": null,
+                "_type": "Array2D"
+            },
+            "label": {
+                "num_classes": 10,
+                "names": [
+                    "0",
+                    "1",
+                    "2",
+                    "3",
+                    "4",
+                    "5",
+                    "6",
+                    "7",
+                    "8",
+                    "9"
+                ],
+                "names_file": null,
+                "id": null,
+                "_type": "ClassLabel"
+            }
+        },
+        "post_processed": null,
+        "supervised_keys": {
+            "input": "image",
+            "output": "label"
+        },
+        "builder_name": "point-cloud-mnist",
+        "config_name": "point-cloud-mnist",
+        "version": {
+            "version_str": "1.0.0",
+            "description": null,
+            "major": 1,
+            "minor": 0,
+            "patch": 0
+        },
+        "splits": {
+            "train": {
+                "name": "train",
+                "num_examples": 60000,
+                "dataset_name": "point-cloud-mnist"
+            },
+            "test": {
+                "name": "test",
+                "num_examples": 10000,
+                "dataset_name": "point-cloud-mnist"
+            }
+        },
+        "post_processing_size": null,
+    }
+}

loading_script.py

@@ -0,0 +1,108 @@
+# coding=utf-8
+
+"""MNIST Point Cloud Data Set"""
+
+
+import struct
+
+import numpy as np
+
+import datasets
+
+_VERSION = "0.0.1"
+
+# _CITATION = """\
+# @article{lecun2010mnist,
+#   title={MNIST handwritten digit database},
+#   author={LeCun, Yann and Cortes, Corinna and Burges, CJ},
+#   journal={ATT Labs [Online]. Available: http://yann.lecun.com/exdb/mnist},
+#   volume={2},
+#   year={2010}
+# }
+# """
+
+_DESCRIPTION = """\
+The MNIST dataset consists of 70,000 28x28 black-and-white points in 10 classes (one for each digits), with 7,000
+points per class. There are 60,000 training points and 10,000 test points.
+"""
+
+_URL = f"https://huggingface.co/datasets/cgarciae/point-cloud-mnist/resolve/{_VERSION}/data/"
+_URLS = {
+    "train_points": "X_train.npy",
+    "train_labels": "y_train.npy",
+    "test_points": "X_test.npy",
+    "test_labels": "y_test.npy",
+}
+
+
+class MNIST(datasets.GeneratorBasedBuilder):
+    """MNIST Data Set"""
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="point-cloud-mnist",
+            version=datasets.Version("1.0.0"),
+            description=_DESCRIPTION,
+        )
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "points": datasets.Array2D(shape=(351, 3), dtype="uint8"),
+                    "label": datasets.features.ClassLabel(
+                        names=["0", "1", "2", "3", "4", "5", "6", "7", "8", "9"]
+                    ),
+                }
+            ),
+            supervised_keys=("points", "label"),
+            # homepage="http://yann.lecun.com/exdb/mnist/",
+            # citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        urls_to_download = {key: _URL + fname for key, fname in _URLS.items()}
+        downloaded_files = dl_manager.download_and_extract(urls_to_download)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": [
+                        downloaded_files["train_points"],
+                        downloaded_files["train_labels"],
+                    ],
+                    "split": "train",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "filepath": [
+                        downloaded_files["test_points"],
+                        downloaded_files["test_labels"],
+                    ],
+                    "split": "test",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath, split):
+        """This function returns the examples in the raw form."""
+        # points
+        with open(filepath[0], "rb") as f:
+            points = np.load(f)
+
+        # Labels
+        with open(filepath[1], "rb") as f:
+            labels = np.load(f)
+
+        for idx in range(len(points)):
+            yield (
+                idx,
+                {
+                    "points": points[idx],
+                    "label": str(labels[idx]),
+                },
+            )

main.py

@@ -1,13 +1,13 @@
-import json
 import os
-from pathlib import Path
 import random
+import typing as tp
+from pathlib import Path
 
 import numpy as np
 import pandas as pd
 import typer
-from tqdm import tqdm
 from datasets.load import load_dataset
+from tqdm import tqdm
 
 np.random.seed(42)
 random.seed(420)
@@ -18,19 +18,17 @@ def main(viz: bool = False):
     dataset = load_dataset("mnist")
     dataset.set_format("np")
     X_train = dataset["train"]["image"]
-    y_train = dataset["train"]["label"]
+    y_train = dataset["train"]["label"].astype(np.uint8)
     X_test = dataset["test"]["image"]
-    y_test = dataset["test"]["label"]
+    y_test = dataset["test"]["label"].astype(np.uint8)
 
-    X_train = to_sparse(X_train)
-    X_test = to_sparse(X_test)
+    Xs_train = to_sparse(X_train)
+    Xs_test = to_sparse(X_test)
 
-    max_length = max(x.shape[0] for x in X_train + X_test)
+    max_length = max(x.shape[0] for x in Xs_train + Xs_test)
 
-    X_train = shuffle_and_pad(X_train, max_length, "train").astype(np.uint8)
-    X_train = X_train.reshape(X_train.shape[0], -1)
-    X_test = shuffle_and_pad(X_test, max_length, "test").astype(np.uint8)
-    X_test = X_test.reshape(X_test.shape[0], -1)
+    X_train = shuffle_and_pad(Xs_train, max_length, "train").astype(np.uint8)
+    X_test = shuffle_and_pad(Xs_test, max_length, "test").astype(np.uint8)
 
     data_path = Path("data")
     np.save(data_path / "X_train.npy", X_train)
@@ -38,51 +36,27 @@ def main(viz: bool = False):
     np.save(data_path / "X_test.npy", X_test)
     np.save(data_path / "y_test.npy", y_test)
 
-    return
-
-    data_train = np.concatenate([y_train[:, None], X_train], axis=-1)
-    data_test = np.concatenate([y_test[:, None], X_test], axis=-1)
-
 
-    columns = [[f"x{i}", f"y{i}", f"v{i}"] for i in range(max_length)]
-    columns = ["label"] + sum(columns, [])
-
-    df_train = pd.DataFrame(data_train, columns=columns)
-    df_test = pd.DataFrame(data_test, columns=columns)
-    test_labels = pd.DataFrame(data_test[:, :1], columns=columns[:1])
-
-    os.makedirs("data/point-cloud-mnist-2D", exist_ok=True)
-
-    print("saving train")
-    df_train.to_csv("data/point-cloud-mnist-2D/train.csv", index=False)
-    print("saving test")
-    df_test.to_csv("data/point-cloud-mnist-2D/test.csv", index=False)
-    print("saving test labels")
-    test_labels.to_csv("data/point-cloud-mnist-2D/test_labels.csv", index=False)
-
-
-def shuffle_and_pad(X, k, name):
+def shuffle_and_pad(Xs, k, name):
 
     samples = []
 
-    padding = np.array([[-1, -1, -1]], dtype=np.int32)
-
-    for x in tqdm(X, desc=f"Padding {name}_{k}"):
+    for x in tqdm(Xs, desc=f"Padding {name}_{k}"):
         N = len(x)
 
         np.random.shuffle(x)
 
         if N < k:
-            x = np.concatenate([x, np.tile(padding, (k - N, 1))])
+            x = np.pad(x, [(0, k - N), (0, 0)])
 
         samples.append(x)
 
-    samples = np.stack(samples, axis=0).astype(np.int32)
+    samples = np.stack(samples, axis=0).astype(np.uint8)
 
     return samples
 
 
-def to_sparse(X: np.ndarray) -> np.ndarray:
+def to_sparse(X: np.ndarray) -> tp.List[np.ndarray]:
 
     N = len(X)
     w, h = X.shape[1:]

poetry.lock

@@ -39,6 +39,34 @@ docs = ["furo", "sphinx", "zope.interface", "sphinx-notfound-page"]
 tests = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins", "zope.interface"]
 tests_no_zope = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins"]
 
+[[package]]
+name = "black"
+version = "21.9b0"
+description = "The uncompromising code formatter."
+category = "dev"
+optional = false
+python-versions = ">=3.6.2"
+
+[package.dependencies]
+click = ">=7.1.2"
+mypy-extensions = ">=0.4.3"
+pathspec = ">=0.9.0,<1"
+platformdirs = ">=2"
+regex = ">=2020.1.8"
+tomli = ">=0.2.6,<2.0.0"
+typed-ast = {version = ">=1.4.2", markers = "python_version < \"3.8\""}
+typing-extensions = [
+    {version = ">=3.10.0.0", markers = "python_version < \"3.10\""},
+    {version = "!=3.10.0.1", markers = "python_version >= \"3.10\""},
+]
+
+[package.extras]
+colorama = ["colorama (>=0.4.3)"]
+d = ["aiohttp (>=3.6.0)", "aiohttp-cors (>=0.4.0)"]
+jupyter = ["ipython (>=7.8.0)", "tokenize-rt (>=3.2.0)"]
+python2 = ["typed-ast (>=1.4.2)"]
+uvloop = ["uvloop (>=0.15.2)"]
+
 [[package]]
 name = "certifi"
 version = "2021.10.8"
@@ -68,11 +96,11 @@ unicode_backport = ["unicodedata2"]
 
 [[package]]
 name = "click"
-version = "7.0"
+version = "7.1.2"
 description = "Composable command line interface toolkit"
 category = "main"
 optional = false
-python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
 
 [[package]]
 name = "colorama"
@@ -109,13 +137,13 @@ xxhash = "*"
 apache-beam = ["apache-beam (>=2.26.0)"]
 audio = ["librosa"]
 benchmarks = ["numpy (==1.18.5)", "tensorflow (==2.3.0)", "torch (==1.6.0)", "transformers (==3.0.2)"]
-dev = ["absl-py", "pytest", "pytest-datadir", "pytest-xdist", "apache-beam (>=2.26.0)", "elasticsearch", "aiobotocore", "boto3", "botocore", "fsspec", "moto[server,s3] (==2.0.4)", "rarfile (>=4.0)", "s3fs (==2021.08.1)", "tensorflow (>=2.3)", "torch", "torchaudio", "transformers", "bs4", "conllu", "langdetect", "lxml", "mwparserfromhell", "nltk", "openpyxl", "py7zr", "tldextract", "zstandard", "bert-score (>=0.3.6)", "rouge-score", "sacrebleu", "scipy", "seqeval", "scikit-learn", "jiwer", "sentencepiece", "toml (>=0.10.1)", "requests-file (>=1.5.1)", "tldextract (>=3.1.0)", "texttable (>=1.6.3)", "Werkzeug (>=1.0.1)", "six (>=1.15.0,<1.16.0)", "black (==21.4b0)", "flake8 (==3.7.9)", "isort", "pyyaml (>=5.3.1)", "importlib-resources"]
+dev = ["absl-py", "pytest", "pytest-datadir", "pytest-xdist", "apache-beam (>=2.26.0)", "elasticsearch", "aiobotocore", "boto3", "botocore", "fsspec", "moto[s3,server] (==2.0.4)", "rarfile (>=4.0)", "s3fs (==2021.08.1)", "tensorflow (>=2.3)", "torch", "torchaudio", "transformers", "bs4", "conllu", "langdetect", "lxml", "mwparserfromhell", "nltk", "openpyxl", "py7zr", "tldextract", "zstandard", "bert-score (>=0.3.6)", "rouge-score", "sacrebleu", "scipy", "seqeval", "scikit-learn", "jiwer", "sentencepiece", "toml (>=0.10.1)", "requests-file (>=1.5.1)", "tldextract (>=3.1.0)", "texttable (>=1.6.3)", "Werkzeug (>=1.0.1)", "six (>=1.15.0,<1.16.0)", "black (==21.4b0)", "flake8 (==3.7.9)", "isort", "pyyaml (>=5.3.1)", "importlib-resources"]
 docs = ["docutils (==0.16.0)", "recommonmark", "sphinx (==3.1.2)", "sphinx-markdown-tables", "sphinx-rtd-theme (==0.4.3)", "sphinxext-opengraph (==0.4.1)", "sphinx-copybutton", "fsspec (<2021.9.0)", "s3fs", "sphinx-panels", "sphinx-inline-tabs", "myst-parser"]
 quality = ["black (==21.4b0)", "flake8 (==3.7.9)", "isort", "pyyaml (>=5.3.1)"]
 s3 = ["fsspec", "boto3", "botocore", "s3fs"]
 tensorflow = ["tensorflow (>=2.2.0)"]
 tensorflow_gpu = ["tensorflow-gpu (>=2.2.0)"]
-tests = ["absl-py", "pytest", "pytest-datadir", "pytest-xdist", "apache-beam (>=2.26.0)", "elasticsearch", "aiobotocore", "boto3", "botocore", "fsspec", "moto[server,s3] (==2.0.4)", "rarfile (>=4.0)", "s3fs (==2021.08.1)", "tensorflow (>=2.3)", "torch", "torchaudio", "transformers", "bs4", "conllu", "langdetect", "lxml", "mwparserfromhell", "nltk", "openpyxl", "py7zr", "tldextract", "zstandard", "bert-score (>=0.3.6)", "rouge-score", "sacrebleu", "scipy", "seqeval", "scikit-learn", "jiwer", "sentencepiece", "toml (>=0.10.1)", "requests-file (>=1.5.1)", "tldextract (>=3.1.0)", "texttable (>=1.6.3)", "Werkzeug (>=1.0.1)", "six (>=1.15.0,<1.16.0)", "importlib-resources"]
+tests = ["absl-py", "pytest", "pytest-datadir", "pytest-xdist", "apache-beam (>=2.26.0)", "elasticsearch", "aiobotocore", "boto3", "botocore", "fsspec", "moto[s3,server] (==2.0.4)", "rarfile (>=4.0)", "s3fs (==2021.08.1)", "tensorflow (>=2.3)", "torch", "torchaudio", "transformers", "bs4", "conllu", "langdetect", "lxml", "mwparserfromhell", "nltk", "openpyxl", "py7zr", "tldextract", "zstandard", "bert-score (>=0.3.6)", "rouge-score", "sacrebleu", "scipy", "seqeval", "scikit-learn", "jiwer", "sentencepiece", "toml (>=0.10.1)", "requests-file (>=1.5.1)", "tldextract (>=3.1.0)", "texttable (>=1.6.3)", "Werkzeug (>=1.0.1)", "six (>=1.15.0,<1.16.0)", "importlib-resources"]
 torch = ["torch"]
 
 [[package]]
@@ -264,6 +292,14 @@ python-versions = "*"
 [package.dependencies]
 dill = ">=0.3.4"
 
+[[package]]
+name = "mypy-extensions"
+version = "0.4.3"
+description = "Experimental type system extensions for programs checked with the mypy typechecker."
+category = "dev"
+optional = false
+python-versions = "*"
+
 [[package]]
 name = "numpy"
 version = "1.18.1"
@@ -299,6 +335,26 @@ pytz = ">=2017.2"
 [package.extras]
 test = ["pytest (>=4.0.2)", "pytest-xdist", "hypothesis (>=3.58)"]
 
+[[package]]
+name = "pathspec"
+version = "0.9.0"
+description = "Utility library for gitignore style pattern matching of file paths."
+category = "dev"
+optional = false
+python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,>=2.7"
+
+[[package]]
+name = "platformdirs"
+version = "2.4.0"
+description = "A small Python module for determining appropriate platform-specific dirs, e.g. a \"user data dir\"."
+category = "dev"
+optional = false
+python-versions = ">=3.6"
+
+[package.extras]
+docs = ["Sphinx (>=4)", "furo (>=2021.7.5b38)", "proselint (>=0.10.2)", "sphinx-autodoc-typehints (>=1.12)"]
+test = ["appdirs (==1.4.4)", "pytest (>=6)", "pytest-cov (>=2.7)", "pytest-mock (>=3.6)"]
+
 [[package]]
 name = "pyarrow"
 version = "6.0.0"
@@ -345,6 +401,14 @@ category = "main"
 optional = false
 python-versions = ">=3.6"
 
+[[package]]
+name = "regex"
+version = "2021.10.23"
+description = "Alternative regular expression module, to replace re."
+category = "dev"
+optional = false
+python-versions = "*"
+
 [[package]]
 name = "requests"
 version = "2.26.0"
@@ -371,6 +435,14 @@ category = "main"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*"
 
+[[package]]
+name = "tomli"
+version = "1.2.2"
+description = "A lil' TOML parser"
+category = "dev"
+optional = false
+python-versions = ">=3.6"
+
 [[package]]
 name = "tqdm"
 version = "4.62.3"
@@ -387,6 +459,14 @@ dev = ["py-make (>=0.1.0)", "twine", "wheel"]
 notebook = ["ipywidgets (>=6)"]
 telegram = ["requests"]
 
+[[package]]
+name = "typed-ast"
+version = "1.4.3"
+description = "a fork of Python 2 and 3 ast modules with type comment support"
+category = "dev"
+optional = false
+python-versions = "*"
+
 [[package]]
 name = "typer"
 version = "0.0.8"
@@ -460,7 +540,7 @@ testing = ["pytest (>=4.6)", "pytest-checkdocs (>=2.4)", "pytest-flake8", "pytes
 [metadata]
 lock-version = "1.1"
 python-versions = "^3.7"
-content-hash = "3b99bb4119b684b68058efc994a72614b795016bd2e54d8ced0e3b48f048ccf4"
+content-hash = "f575d3c626ec7e75b4cff3341bd4c5d3b722846e1ec40351b11767ab51c43e46"
 
 [metadata.files]
 aiohttp = [
@@ -510,6 +590,10 @@ attrs = [
     {file = "attrs-21.2.0-py2.py3-none-any.whl", hash = "sha256:149e90d6d8ac20db7a955ad60cf0e6881a3f20d37096140088356da6c716b0b1"},
     {file = "attrs-21.2.0.tar.gz", hash = "sha256:ef6aaac3ca6cd92904cdd0d83f629a15f18053ec84e6432106f7a4d04ae4f5fb"},
 ]
+black = [
+    {file = "black-21.9b0-py3-none-any.whl", hash = "sha256:380f1b5da05e5a1429225676655dddb96f5ae8c75bdf91e53d798871b902a115"},
+    {file = "black-21.9b0.tar.gz", hash = "sha256:7de4cfc7eb6b710de325712d40125689101d21d25283eed7e9998722cf10eb91"},
+]
 certifi = [
     {file = "certifi-2021.10.8-py2.py3-none-any.whl", hash = "sha256:d62a0163eb4c2344ac042ab2bdf75399a71a2d8c7d47eac2e2ee91b9d6339569"},
     {file = "certifi-2021.10.8.tar.gz", hash = "sha256:78884e7c1d4b00ce3cea67b44566851c4343c120abd683433ce934a68ea58872"},
@@ -523,8 +607,8 @@ charset-normalizer = [
     {file = "charset_normalizer-2.0.7-py3-none-any.whl", hash = "sha256:f7af805c321bfa1ce6714c51f254e0d5bb5e5834039bc17db7ebe3a4cec9492b"},
 ]
 click = [
-    {file = "Click-7.0-py2.py3-none-any.whl", hash = "sha256:2335065e6395b9e67ca716de5f7526736bfa6ceead690adf616d925bdc622b13"},
-    {file = "Click-7.0.tar.gz", hash = "sha256:5b94b49521f6456670fdb30cd82a4eca9412788a93fa6dd6df72c94d5a8ff2d7"},
+    {file = "click-7.1.2-py2.py3-none-any.whl", hash = "sha256:dacca89f4bfadd5de3d7489b7c8a566eee0d3676333fbb50030263894c38c0dc"},
+    {file = "click-7.1.2.tar.gz", hash = "sha256:d2b5255c7c6349bc1bd1e59e08cd12acbbd63ce649f2588755783aa94dfb6b1a"},
 ]
 colorama = [
     {file = "colorama-0.4.4-py2.py3-none-any.whl", hash = "sha256:9f47eda37229f68eee03b24b9748937c7dc3868f906e8ba69fbcbdd3bc5dc3e2"},
@@ -673,6 +757,10 @@ multiprocess = [
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 ]
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+]
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@@ -716,6 +804,14 @@ pandas = [
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 ]
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+]
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@@ -801,6 +897,44 @@ pyyaml = [
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 ]
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@@ -809,10 +943,46 @@ six = [
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 ]
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 tqdm = [
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pyproject.toml

@@ -15,6 +15,7 @@ datasets = "^1.14.0"
 
 [tool.poetry.dev-dependencies]
 debugpy = "^1.5.1"
+black = {version = "^21.9b0", allow-prereleases = true}
 
 [build-system]
 requires = ["poetry>=0.12"]