Changes: - CLAUDE.md: Update OOM fix validation status - Add comprehensive documentation (30+ markdown reports) - LSTM encoder varmap bug fix (tft/lstm_encoder.rs:290) - Quantized LSTM layer matching fix (tft/quantized_lstm.rs) - Hyperopt paths module (ml/src/hyperopt/paths.rs) - Training path tests for all adapters (DQN, MAMBA-2, PPO, TFT) - Checkpoint integrity tests - Script cleanup: Remove 29 obsolete deployment scripts - Archive old scripts to scripts/archive/ - New deployment utilities: check_gpu_availability.py, monitor_hyperopt.sh Validation: - OOM fixes validated: 5/5 trials successful (pod b6kc3mc5lbjiro) - Batch-size-max 256 tested successfully - All hyperopt adapters working correctly 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
332 lines
11 KiB
Bash
Executable File
332 lines
11 KiB
Bash
Executable File
#!/bin/bash
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################################################################################
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# runpod_upload.sh - Upload Foxhunt binaries and data to Runpod Network Volume
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#
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# Purpose:
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# Builds release binaries with CUDA support and uploads them to Runpod
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# Network Volume using AWS S3-compatible API. This script runs on LOCAL
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# CLIENT ONLY. Runpod pods will mount the volume and access files at
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# /runpod-volume/.
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#
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# Prerequisites:
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# 1. AWS CLI installed: apt-get install awscli
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# 2. Runpod credentials configured in ~/.aws/credentials:
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# [runpod]
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# aws_access_key_id = <your-runpod-user-id>
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# aws_secret_access_key = <your-runpod-api-key>
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# 3. Environment variable RUNPOD_S3_ENDPOINT set to your Runpod endpoint
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# Example: export RUNPOD_S3_ENDPOINT="https://s3api-eur-is-1.runpod.io"
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#
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# Environment Variables:
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# - RUNPOD_S3_ENDPOINT: Runpod S3-compatible endpoint (required)
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# - AWS_PROFILE: AWS profile to use (default: runpod)
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#
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# Usage:
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# export RUNPOD_S3_ENDPOINT="https://s3api-eur-is-1.runpod.io"
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# ./scripts/runpod_upload.sh
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#
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# What gets uploaded:
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# - Release binaries: train_tft_parquet, train_dqn, train_ppo, train_mamba2_dbn
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# - Test data: 9 Parquet files (ES.FUT, NQ.FUT, 6E.FUT, ZN.FUT variants)
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# - Directory structure: /runpod-volume/{bin,test_data,models}
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#
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# Post-upload access on Runpod pod:
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# - Binaries: /runpod-volume/bin/train_tft_parquet
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# - Data: /runpod-volume/test_data/ES_FUT_180d.parquet
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# - Models: /runpod-volume/models/ (for trained output)
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################################################################################
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set -e # Exit on any error
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# ANSI color codes for output formatting
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RED='\033[0;31m'
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GREEN='\033[0;32m'
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YELLOW='\033[0;33m'
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BLUE='\033[0;34m'
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BOLD='\033[1m'
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NC='\033[0m' # No Color
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################################################################################
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# Configuration Validation
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################################################################################
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echo -e "${BOLD}=========================================${NC}"
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echo -e "${BOLD}Foxhunt Runpod Upload Script${NC}"
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echo -e "${BOLD}=========================================${NC}"
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echo ""
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# Validate RUNPOD_S3_ENDPOINT environment variable
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if [ -z "$RUNPOD_S3_ENDPOINT" ]; then
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echo -e "${RED}ERROR: RUNPOD_S3_ENDPOINT environment variable not set${NC}"
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echo ""
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echo "Please set your Runpod S3 endpoint:"
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echo " export RUNPOD_S3_ENDPOINT=\"https://s3api-<datacenter>.runpod.io\""
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echo ""
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echo "Find your endpoint in Runpod console:"
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echo " 1. Go to https://www.runpod.io/console/user/settings"
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echo " 2. Navigate to 'Network Volumes'"
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echo " 3. Copy the S3 endpoint URL"
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exit 1
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fi
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# Set AWS profile (default: runpod)
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AWS_PROFILE="${AWS_PROFILE:-runpod}"
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# Validate AWS profile exists
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if ! aws configure list --profile "$AWS_PROFILE" &>/dev/null; then
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echo -e "${RED}ERROR: AWS profile '$AWS_PROFILE' not found${NC}"
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echo ""
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echo "Please configure Runpod credentials in ~/.aws/credentials:"
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echo " [runpod]"
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echo " aws_access_key_id = <your-runpod-user-id>"
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echo " aws_secret_access_key = <your-runpod-api-key>"
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echo ""
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echo "Find your credentials in Runpod console:"
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echo " 1. Go to https://www.runpod.io/console/user/settings"
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echo " 2. Navigate to 'API Keys'"
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echo " 3. Copy User ID and API Key"
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exit 1
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fi
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# Configuration summary
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echo -e "${BLUE}Configuration:${NC}"
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echo " Endpoint: $RUNPOD_S3_ENDPOINT"
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echo " AWS Profile: $AWS_PROFILE"
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echo " Upload Target: s3://runpod-volume/foxhunt/"
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echo ""
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# Project root directory
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FOXHUNT_ROOT="$(cd "$(dirname "$0")/.." && pwd)"
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cd "$FOXHUNT_ROOT"
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################################################################################
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# Step 1: Build Release Binaries with CUDA
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################################################################################
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echo -e "${BOLD}Step 1/5: Building release binaries with CUDA support...${NC}"
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echo "This may take 5-10 minutes depending on system."
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echo ""
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START_TIME=$(date +%s)
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# Build with release profile and CUDA features
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if cargo build --release --features cuda --workspace; then
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END_TIME=$(date +%s)
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BUILD_DURATION=$((END_TIME - START_TIME))
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BUILD_MIN=$(awk "BEGIN {printf \"%.2f\", $BUILD_DURATION/60}")
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echo -e "${GREEN}✅ Build complete in ${BUILD_MIN} minutes${NC}"
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else
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echo -e "${RED}❌ ERROR: Cargo build failed${NC}"
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echo "Debug steps:"
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echo " 1. Check Rust toolchain: rustc --version"
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echo " 2. Verify CUDA installation: nvidia-smi"
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echo " 3. Check build logs above for specific errors"
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exit 1
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fi
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echo ""
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################################################################################
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# Step 2: Upload Training Binaries
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################################################################################
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echo -e "${BOLD}Step 2/5: Uploading training binaries...${NC}"
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echo ""
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# List of training binaries to upload
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BINARIES=(
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"train_tft_parquet"
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"train_dqn"
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"train_ppo"
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"train_mamba2_dbn"
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)
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TOTAL_BIN_SIZE=0
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UPLOADED_COUNT=0
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for binary in "${BINARIES[@]}"; do
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SRC="$FOXHUNT_ROOT/target/release/examples/$binary"
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if [ -f "$SRC" ]; then
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# Get file size
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SIZE=$(stat -c%s "$SRC" 2>/dev/null || stat -f%z "$SRC" 2>/dev/null)
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SIZE_MB=$(awk "BEGIN {printf \"%.2f\", $SIZE/1024/1024}")
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TOTAL_BIN_SIZE=$((TOTAL_BIN_SIZE + SIZE))
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# Upload to Runpod S3
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DEST="s3://se3zdnb5o4/binaries/$binary"
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if aws s3 cp "$SRC" "$DEST" \
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--profile "$AWS_PROFILE" \
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--endpoint-url "$RUNPOD_S3_ENDPOINT"; then
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echo -e " ${GREEN}✓${NC} $binary (${SIZE_MB} MB)"
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UPLOADED_COUNT=$((UPLOADED_COUNT + 1))
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else
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echo -e " ${RED}✗${NC} $binary upload failed"
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fi
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else
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echo -e " ${YELLOW}⚠${NC} $binary not found (skipping)"
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fi
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done
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TOTAL_BIN_MB=$(awk "BEGIN {printf \"%.2f\", $TOTAL_BIN_SIZE/1024/1024}")
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echo ""
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echo "Uploaded $UPLOADED_COUNT binaries (${TOTAL_BIN_MB} MB total)"
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echo ""
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################################################################################
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# Step 3: Upload Test Data (Parquet Files)
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################################################################################
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echo -e "${BOLD}Step 3/5: Uploading test data (Parquet files)...${NC}"
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echo ""
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PARQUET_FILES=(
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"ES_FUT_180d.parquet"
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"NQ_FUT_180d.parquet"
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"6E_FUT_180d.parquet"
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"ZN_FUT_90d.parquet"
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"ZN_FUT_90d_clean.parquet"
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"ES_FUT_small.parquet"
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"NQ_FUT_small.parquet"
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"6E_FUT_small.parquet"
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"ZN_FUT_small.parquet"
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)
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TOTAL_DATA_SIZE=0
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UPLOADED_DATA_COUNT=0
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for file in "${PARQUET_FILES[@]}"; do
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SRC="$FOXHUNT_ROOT/test_data/$file"
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if [ -f "$SRC" ]; then
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# Get file size
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SIZE=$(stat -c%s "$SRC" 2>/dev/null || stat -f%z "$SRC" 2>/dev/null)
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SIZE_MB=$(awk "BEGIN {printf \"%.2f\", $SIZE/1024/1024}")
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TOTAL_DATA_SIZE=$((TOTAL_DATA_SIZE + SIZE))
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# Upload to Runpod S3
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DEST="s3://se3zdnb5o4/test_data/$file"
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if aws s3 cp "$SRC" "$DEST" \
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--profile "$AWS_PROFILE" \
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--endpoint-url "$RUNPOD_S3_ENDPOINT"; then
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echo -e " ${GREEN}✓${NC} $file (${SIZE_MB} MB)"
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UPLOADED_DATA_COUNT=$((UPLOADED_DATA_COUNT + 1))
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else
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echo -e " ${RED}✗${NC} $file upload failed"
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fi
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else
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echo -e " ${YELLOW}⚠${NC} $file not found (skipping)"
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fi
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done
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TOTAL_DATA_MB=$(awk "BEGIN {printf \"%.2f\", $TOTAL_DATA_SIZE/1024/1024}")
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echo ""
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echo "Uploaded $UPLOADED_DATA_COUNT data files (${TOTAL_DATA_MB} MB total)"
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echo ""
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################################################################################
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# Step 4: Create Models Directory
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################################################################################
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echo -e "${BOLD}Step 4/5: Creating /runpod-volume/models/ directory...${NC}"
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echo ""
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# Create empty marker file to ensure directory exists
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MARKER_FILE=$(mktemp)
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echo "Model storage directory created by runpod_upload.sh" > "$MARKER_FILE"
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echo "Date: $(date)" >> "$MARKER_FILE"
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if aws s3 cp "$MARKER_FILE" "s3://se3zdnb5o4/models/.directory_created" \
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--profile "$AWS_PROFILE" \
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--endpoint-url "$RUNPOD_S3_ENDPOINT"; then
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echo -e "${GREEN}✅ Models directory created${NC}"
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else
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echo -e "${YELLOW}⚠ Warning: Could not create models directory marker${NC}"
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fi
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rm -f "$MARKER_FILE"
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echo ""
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################################################################################
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# Step 5: Verify Uploads
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################################################################################
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echo -e "${BOLD}Step 5/5: Verifying uploads...${NC}"
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echo ""
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# List uploaded files to verify
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echo "Verifying binaries/ directory:"
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if aws s3 ls "s3://se3zdnb5o4/binaries/" \
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--profile "$AWS_PROFILE" \
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--endpoint-url "$RUNPOD_S3_ENDPOINT" | head -10; then
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echo -e "${GREEN}✅ Binaries verified${NC}"
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else
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echo -e "${RED}❌ Could not verify binaries${NC}"
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fi
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echo ""
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echo "Verifying test_data/ directory:"
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if aws s3 ls "s3://se3zdnb5o4/test_data/" \
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--profile "$AWS_PROFILE" \
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--endpoint-url "$RUNPOD_S3_ENDPOINT" | head -10; then
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echo -e "${GREEN}✅ Test data verified${NC}"
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else
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echo -e "${RED}❌ Could not verify test data${NC}"
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fi
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echo ""
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echo "Verifying models/ directory:"
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if aws s3 ls "s3://se3zdnb5o4/models/" \
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--profile "$AWS_PROFILE" \
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--endpoint-url "$RUNPOD_S3_ENDPOINT" | head -5; then
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echo -e "${GREEN}✅ Models directory verified${NC}"
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else
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echo -e "${YELLOW}⚠ Warning: Models directory not found (non-critical)${NC}"
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fi
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################################################################################
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# Upload Summary
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################################################################################
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echo ""
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echo -e "${BOLD}=========================================${NC}"
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echo -e "${BOLD}${GREEN}✅ Upload Complete!${NC}${BOLD}${NC}"
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echo -e "${BOLD}=========================================${NC}"
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echo ""
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echo -e "${BLUE}Upload Summary:${NC}"
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echo " Binaries: $UPLOADED_COUNT files (${TOTAL_BIN_MB} MB)"
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echo " Test Data: $UPLOADED_DATA_COUNT files (${TOTAL_DATA_MB} MB)"
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TOTAL_SIZE_MB=$(awk "BEGIN {printf \"%.2f\", ($TOTAL_BIN_SIZE + $TOTAL_DATA_SIZE)/1024/1024}")
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echo " Total: ${TOTAL_SIZE_MB} MB"
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echo ""
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echo -e "${BLUE}Files available at (on Runpod pod):${NC}"
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echo " Binaries: /runpod-volume/binaries/"
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echo " Test Data: /runpod-volume/test_data/"
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echo " Models (output): /runpod-volume/models/"
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echo ""
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echo -e "${BLUE}Next Steps:${NC}"
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echo "1. Create Runpod pod with Tesla V100 16GB GPU"
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echo "2. Mount network volume (se3zdnb5o4) to /runpod-volume"
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echo "3. Run training on pod:"
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echo " cd /runpod-volume"
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echo " ./binaries/train_tft_parquet \\"
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echo " --parquet-file ./test_data/ES_FUT_180d.parquet \\"
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echo " --epochs 50 \\"
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echo " --output-dir ./models/tft_fp32"
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echo ""
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echo -e "${BLUE}To download trained models:${NC}"
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echo " aws s3 sync \\"
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echo " --profile runpod \\"
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echo " --endpoint-url $RUNPOD_S3_ENDPOINT \\"
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echo " s3://se3zdnb5o4/models/ ./models/"
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echo ""
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echo -e "${BOLD}=========================================${NC}"
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echo -e "${GREEN}Ready for Runpod deployment!${NC}"
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echo -e "${BOLD}=========================================${NC}"
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