#!/usr/bin/env python3
"""
Performance tests for ROCM Ninodes
Tests timing and memory usage requirements
"""

import time
import pytest
import torch
from .test_fixtures import (
    load_flux_checkpoint_data, load_flux_ksampler_data, load_flux_vae_data,
    load_wan_ksampler_data, load_wan_vae_data,
    load_timing_data, load_memory_data,
    create_mock_latent, create_mock_video_latent, create_mock_image_latent
)

# Performance targets (in seconds)
PERFORMANCE_TARGETS = {
    'flux_checkpoint_load': 30.0,
    'flux_ksampler': 60.0,
    'flux_vae_decode': 10.0,
    'wan_ksampler': 100.0,
    'wan_vae_decode': 10.0,
}

class TestFluxPerformance:
    """Performance tests for Flux workflow components"""
    
    def test_flux_checkpoint_loader_performance(self):
        """Test checkpoint loader performance meets target"""
        data = load_flux_checkpoint_data()
        if data is None:
            pytest.skip("No captured checkpoint data available")
        
        # Mock checkpoint loader execution
        start_time = time.time()
        
        # Simulate checkpoint loading work
        time.sleep(0.1)  # Simulate processing time
        
        elapsed = time.time() - start_time
        
        assert elapsed < PERFORMANCE_TARGETS['flux_checkpoint_load'], \
            f"Checkpoint load too slow: {elapsed:.2f}s (target: {PERFORMANCE_TARGETS['flux_checkpoint_load']}s)"
    
    def test_flux_ksampler_performance(self):
        """Test KSampler performance meets target"""
        data = load_flux_ksampler_data()
        if data is None:
            pytest.skip("No captured KSampler data available")
        
        # Mock KSampler execution
        start_time = time.time()
        
        # Simulate sampling work
        time.sleep(0.1)  # Simulate processing time
        
        elapsed = time.time() - start_time
        
        assert elapsed < PERFORMANCE_TARGETS['flux_ksampler'], \
            f"KSampler too slow: {elapsed:.2f}s (target: {PERFORMANCE_TARGETS['flux_ksampler']}s)"
    
    def test_flux_vae_decode_performance(self):
        """Test VAE decode performance meets target"""
        data = load_flux_vae_data()
        if data is None:
            pytest.skip("No captured VAE data available")
        
        # Mock VAE decode execution
        start_time = time.time()
        
        # Simulate VAE decode work
        time.sleep(0.1)  # Simulate processing time
        
        elapsed = time.time() - start_time
        
        assert elapsed < PERFORMANCE_TARGETS['flux_vae_decode'], \
            f"VAE decode too slow: {elapsed:.2f}s (target: {PERFORMANCE_TARGETS['flux_vae_decode']}s)"

class TestWANPerformance:
    """Performance tests for WAN workflow components"""
    
    def test_wan_ksampler_performance(self):
        """Test WAN KSampler performance meets target"""
        data = load_wan_ksampler_data()
        if data is None:
            pytest.skip("No captured WAN KSampler data available")
        
        # Mock KSampler execution
        start_time = time.time()
        
        # Simulate sampling work
        time.sleep(0.1)  # Simulate processing time
        
        elapsed = time.time() - start_time
        
        assert elapsed < PERFORMANCE_TARGETS['wan_ksampler'], \
            f"WAN KSampler too slow: {elapsed:.2f}s (target: {PERFORMANCE_TARGETS['wan_ksampler']}s)"
    
    def test_wan_vae_decode_performance(self):
        """Test WAN VAE decode performance meets target"""
        data = load_wan_vae_data()
        if data is None:
            pytest.skip("No captured WAN VAE data available")
        
        # Mock VAE decode execution
        start_time = time.time()
        
        # Simulate VAE decode work
        time.sleep(0.1)  # Simulate processing time
        
        elapsed = time.time() - start_time
        
        assert elapsed < PERFORMANCE_TARGETS['wan_vae_decode'], \
            f"WAN VAE decode too slow: {elapsed:.2f}s (target: {PERFORMANCE_TARGETS['wan_vae_decode']}s)"

class TestMemoryUsage:
    """Memory usage tests"""
    
    def test_memory_usage_reasonable(self):
        """Test that memory usage is within reasonable bounds"""
        # This would need actual implementation to test memory usage
        # For now, just verify we can check memory if available
        if torch.cuda.is_available():
            memory_allocated = torch.cuda.memory_allocated()
            memory_reserved = torch.cuda.memory_reserved()
            
            # Basic sanity checks
            assert memory_allocated >= 0, "Memory allocated should be non-negative"
            assert memory_reserved >= 0, "Memory reserved should be non-negative"
            assert memory_reserved >= memory_allocated, "Reserved memory should be >= allocated"

class TestPerformanceRegression:
    """Tests to prevent performance regression"""
    
    def test_no_performance_regression(self):
        """Test that performance hasn't regressed significantly"""
        # This would compare against baseline performance
        # For now, just verify the test framework works
        assert True, "Performance regression test placeholder"
    
    def test_timing_data_available(self):
        """Test that timing data is being captured"""
        # Check if we have any timing data
        timing_functions = ['checkpoint_loader', 'ksampler', 'vae_decode']
        has_timing_data = False
        
        for func in timing_functions:
            timing_data = load_timing_data(func)
            if timing_data is not None:
                has_timing_data = True
                break
        
        # This test will pass even without data, but logs the status
        if not has_timing_data:
            print("Warning: No timing data available for regression testing")

class TestMockDataPerformance:
    """Performance tests using mock data when captured data is unavailable"""
    
    def test_mock_flux_vae_performance(self):
        """Test VAE decode performance with mock data"""
        # Create mock Flux VAE input (4D tensor)
        mock_data = create_mock_image_latent(batch_size=1, channels=16, height=128, width=128)
        
        start_time = time.time()
        
        # Simulate VAE decode work
        time.sleep(0.1)  # Simulate processing time
        
        elapsed = time.time() - start_time
        
        assert elapsed < PERFORMANCE_TARGETS['flux_vae_decode'], \
            f"Mock VAE decode too slow: {elapsed:.2f}s (target: {PERFORMANCE_TARGETS['flux_vae_decode']}s)"
    
    def test_mock_wan_vae_performance(self):
        """Test WAN VAE decode performance with mock data"""
        # Create mock WAN VAE input (5D tensor)
        mock_data = create_mock_video_latent(batch_size=1, channels=16, frames=17, height=32, width=32)
        
        start_time = time.time()
        
        # Simulate VAE decode work
        time.sleep(0.1)  # Simulate processing time
        
        elapsed = time.time() - start_time
        
        assert elapsed < PERFORMANCE_TARGETS['wan_vae_decode'], \
            f"Mock WAN VAE decode too slow: {elapsed:.2f}s (target: {PERFORMANCE_TARGETS['wan_vae_decode']}s)"

if __name__ == "__main__":
    pytest.main([__file__, "-v"])