From: François Fleuret <francois@fleuret.org>
Date: Tue, 26 Mar 2024 18:55:44 +0000 (+0100)
Subject: Update.
X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=commitdiff_plain;h=ffeb45668535e2c338feb5dfb50c4d0ab22ae2a9;p=pytorch.git

Update.
---

diff --git a/bit_mlp.py b/bit_mlp.py
index 90409f2..6f7f92e 100755
--- a/bit_mlp.py
+++ b/bit_mlp.py
@@ -116,33 +116,40 @@ for linear_layer in errors.keys():
 
         ######################################################################
 
-        errors[linear_layer].append((nb_hidden, test_error))
+        errors[linear_layer].append(
+            (nb_hidden, test_error * 100, acc_train_loss / train_input.size(0))
+        )
 
 import matplotlib.pyplot as plt
 
-fig = plt.figure()
-fig.set_figheight(6)
-fig.set_figwidth(8)
 
-ax = fig.add_subplot(1, 1, 1)
+def save_fig(filename, ymax, ylabel, index):
+    fig = plt.figure()
+    fig.set_figheight(6)
+    fig.set_figwidth(8)
 
-ax.set_ylim(0, 1)
-ax.spines.right.set_visible(False)
-ax.spines.top.set_visible(False)
-ax.set_xscale("log")
-ax.set_xlabel("Nb hidden units")
-ax.set_ylabel("Test error (%)")
+    ax = fig.add_subplot(1, 1, 1)
 
-X = torch.tensor([x[0] for x in errors[nn.Linear]])
-Y = torch.tensor([x[1] for x in errors[nn.Linear]])
-ax.plot(X, Y, color="gray", label="nn.Linear")
+    ax.set_ylim(0, ymax)
+    ax.spines.right.set_visible(False)
+    ax.spines.top.set_visible(False)
+    ax.set_xscale("log")
+    ax.set_xlabel("Nb hidden units")
+    ax.set_ylabel(ylabel)
 
-X = torch.tensor([x[0] for x in errors[QLinear]])
-Y = torch.tensor([x[1] for x in errors[QLinear]])
-ax.plot(X, Y, color="red", label="QLinear")
+    X = torch.tensor([x[0] for x in errors[nn.Linear]])
+    Y = torch.tensor([x[index] for x in errors[nn.Linear]])
+    ax.plot(X, Y, color="gray", label="nn.Linear")
 
-ax.legend(frameon=False, loc=1)
+    X = torch.tensor([x[0] for x in errors[QLinear]])
+    Y = torch.tensor([x[index] for x in errors[QLinear]])
+    ax.plot(X, Y, color="red", label="QLinear")
 
-filename = f"bit_mlp.pdf"
-print(f"saving {filename}")
-fig.savefig(filename, bbox_inches="tight")
+    ax.legend(frameon=False, loc=1)
+
+    print(f"saving {filename}")
+    fig.savefig(filename, bbox_inches="tight")
+
+
+save_fig("bit_mlp_err.pdf", ymax=15, ylabel="Test error (%)", index=1)
+save_fig("bit_mlp_loss.pdf", ymax=1.25, ylabel="Train loss", index=2)