refactor: Standardize imports across modules 10-17 to match 01-09

Enforce consistent import pattern across all modules:
- Direct imports from tinytorch.core.* (no fallbacks)
- Remove all sys.path.append manipulations
- Remove try/except import fallbacks
- Remove mock/dummy class fallbacks

Fixed modules:
- Module 10 (tokenization): Removed try/except fallback
- Module 12 (attention): Removed sys.path.append for tensor/layers
- Module 15 (profiling): Removed sys.path + mock Tensor/Linear/Conv2d
- Module 16 (acceleration): Removed hardcoded path + importlib + mock Tensor
- Module 17 (quantization): Removed sys.path + disabled fallback block

All modules now follow the same pattern as modules 01-09:
  from tinytorch.core.tensor import Tensor
  from tinytorch.core.layers import Linear
  # etc.

No development fallbacks - assume tinytorch package is installed.

modules/source/17_quantization/quantization_dev.py

@@ -69,61 +69,10 @@ import matplotlib.pyplot as plt
 from typing import Tuple, Dict, List, Optional
 import warnings
 
-# Smart import system for development and production compatibility
-import sys
-import os
-
 # Import dependencies from other modules
-sys.path.append(os.path.join(os.path.dirname(__file__), '..', '01_tensor'))
-from tensor_dev import Tensor
-
-sys.path.append(os.path.join(os.path.dirname(__file__), '..', '03_layers'))
-from layers_dev import Linear, Sequential
-
-sys.path.append(os.path.join(os.path.dirname(__file__), '..', '02_activations'))
-from activations_dev import ReLU
-
-# Note: Keeping development fallback for reference
-if False:  # Disabled development fallback
-    # Development: Import from local module files
-    try:
-        # Try to find the current directory
-        current_dir = os.path.dirname(os.path.abspath(__file__))
-    except NameError:
-        # Fallback when __file__ is not available (e.g., in exec context)
-        current_dir = os.getcwd()
-
-    # Import Tensor from Module 01
-    tensor_module_path = os.path.join(current_dir, '..', '01_tensor')
-    sys.path.insert(0, tensor_module_path)
-    try:
-        from tensor_dev import Tensor
-    finally:
-        sys.path.pop(0)
-
-    # Import from Module 03 layers
-    layers_module_path = os.path.join(current_dir, '..', '03_layers')
-    sys.path.insert(0, layers_module_path)
-    try:
-        from layers_dev import Linear, Sequential
-    finally:
-        sys.path.pop(0)
-
-    # Import from Module 02 activations
-    activations_module_path = os.path.join(current_dir, '..', '02_activations')
-    sys.path.insert(0, activations_module_path)
-    try:
-        from activations_dev import ReLU
-    finally:
-        sys.path.pop(0)
-
-    # Create dummy profiler if needed
-    class Profiler:
-        """Dummy profiler class for development."""
-        def count_parameters(self, model):
-            return 0
-        def measure_memory(self, model, input_shape):
-            return {"total": 0}
+from tinytorch.core.tensor import Tensor
+from tinytorch.core.layers import Linear
+from tinytorch.core.activations import ReLU
 
 print("✅ Quantization module imports complete")