Create Dockerfile

Dockerfile

@@ -0,0 +1,54 @@
+# Use NVIDIA CUDA base image
+FROM nvidia/cuda:12.4.1-cudnn-devel-ubuntu22.04
+
+# Set the maintainer label
+LABEL maintainer="[email protected]" \
+      version="0.1" \
+      description="Robotics Diffusion Transformer with CUDA 12.4.1 support"
+
+# Set environment variables
+ENV LC_ALL=C.UTF-8 \
+    LANG=C.UTF-8 \
+    PYTHON_VERSION=3.10 \
+    TZ=Europe/Rome
+
+# Install system dependencies
+RUN ln -snf /usr/share/zoneinfo/$TZ /etc/localtime && echo $TZ > /etc/timezone && \
+    apt-get update && apt-get install -y --no-install-recommends \
+    git \
+    python3.10 \
+    python3-pip \
+    python3.10-dev \
+    && rm -rf /var/lib/apt/lists/*
+
+# Set working directory
+WORKDIR /app
+
+# Install Python dependencies in correct order
+RUN pip3 install --no-cache-dir --upgrade pip setuptools wheel && \
+    pip3 install --no-cache-dir "numpy<2"  # Force NumPy 1.x version
+
+# Install PyTorch with CUDA 12.1
+RUN pip3 install --no-cache-dir \
+    torch==2.1.0+cu121 \
+    torchvision==0.16.0+cu121 \
+    --index-url https://download.pytorch.org/whl/cu121
+
+# Install packaging and other dependencies
+RUN pip3 install --no-cache-dir \
+    packaging==24.0 \
+    transformers \
+    diffusers
+
+# Install flash-attn with build constraints
+RUN pip3 install --no-cache-dir flash-attn==2.5.7 --no-build-isolation
+
+# Copy requirements and install remaining packages
+COPY requirements.txt .
+RUN pip3 install --no-cache-dir -r requirements.txt
+
+# Copy project files
+COPY . .
+
+# Set default command
+CMD ["python3", "-u", "main.py"]