add torchsummary, verify a few notebooks

.gitignore

 datascienceintro/imagenet_class_index.json
 datascienceintro/data/qm9
 datascienceintro/data/mnist
+datascienceintro/solutions/data/mnist/MNIST/raw/t10k-images-idx3-ubyte
+datascienceintro/solutions/data/mnist/MNIST/raw/t10k-images-idx3-ubyte.gz
+datascienceintro/solutions/data/mnist/MNIST/raw/t10k-labels-idx1-ubyte
+datascienceintro/solutions/data/mnist/MNIST/raw/t10k-labels-idx1-ubyte.gz
+datascienceintro/solutions/data/mnist/MNIST/raw/train-images-idx3-ubyte
+datascienceintro/solutions/data/mnist/MNIST/raw/train-images-idx3-ubyte.gz
+datascienceintro/solutions/data/mnist/MNIST/raw/train-labels-idx1-ubyte
+datascienceintro/solutions/data/mnist/MNIST/raw/train-labels-idx1-ubyte.gz

poetry.lock

@@ -3551,6 +3551,18 @@ files = [
 [package.dependencies]
 torch = "2.6.0"
 
+[[package]]
+name = "torchsummary"
+version = "1.5.1"
+description = "Model summary in PyTorch similar to `model.summary()` in Keras"
+optional = false
+python-versions = "*"
+groups = ["main"]
+files = [
+    {file = "torchsummary-1.5.1-py3-none-any.whl", hash = "sha256:10f41d1743fb918f83293f13183f532ab1bb8f6639a1b89e5f8592ec1919a976"},
+    {file = "torchsummary-1.5.1.tar.gz", hash = "sha256:981bf689e22e0cf7f95c746002f20a24ad26aa6b9d861134a14bc6ce92230590"},
+]
+
 [[package]]
 name = "torchvision"
 version = "0.21.0"
@@ -3795,4 +3807,4 @@ test = ["websockets"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.11,<3.12"
-content-hash = "45f6df7976ef37dd19d59cc78a471cb43d45f21f030a28e64f49cc276f6f1482"
+content-hash = "c352f0d569c2f4565ec4e3e279904127a1e8078d3a7118eca86dabe79f1d2de9"

pyproject.toml

@@ -25,6 +25,7 @@ scikit-image = "^0.25.2"
 cyclic-boosting = "^1.4.0"
 ipython = "^9.0.2"
 attrs = "^25.2.0"
+torchsummary = "^1.5.1"
 
 
 [tool.poetry.group.dev.dependencies]