Improved parameter counting and model summary utilities with detailed… #3

	name: MNIST Model Tests

	on:
	push:
	paths:
	- 'MNIST_99.4/**'
	branches: [ main ]
	pull_request:
	paths:
	- 'MNIST_99.4/**'
	branches: [ main ]

	jobs:
	test:
	runs-on: ubuntu-latest

	defaults:
	run:
	working-directory: ./MNIST_99.4

	steps:
	- uses: actions/checkout@v2

	- name: Set up Python
	uses: actions/setup-python@v2
	with:
	python-version: '3.8'

	- name: Install dependencies
	run: \|
	python -m pip install --upgrade pip
	pip install torch torchvision pytest

	- name: Run tests
	run: \|
	python -m pytest tests/test_model.py -v

	- name: Verify model architecture
	run: \|
	python -c "
	from models.model import MNISTModel
	from utils import count_parameters, has_batch_norm, has_dropout, has_fully_connected

	model = MNISTModel()

	# Check parameters count
	assert count_parameters(model) <= 20000, 'Model exceeds 20k parameters'

	# Check architecture requirements
	assert has_batch_norm(model), 'Missing Batch Normalization'
	assert has_dropout(model), 'Missing Dropout'
	assert has_fully_connected(model), 'Missing Fully Connected Layer'

	print('All architecture checks passed!')"

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