Fix flaky TestLoadJIT_3 by relaxing allclose tolerances (#1527)

The 1000->100 linear layer sums 1000 float32 values per output neuron.
Under varying CPU load, parallel BLAS libraries change reduction thread
scheduling, altering FP summation order and exceeding the tight default
tolerances (rtol=1e-5, atol=1e-8). Relax to rtol=1e-4, atol=1e-5,
consistent with patterns used elsewhere in the test suite.

Author: alinpahontu2912

test/TorchSharpTest/TestJIT.cs

@@ -161,7 +161,7 @@ public void TestLoadJIT_3()
 
             Assert.Equal(new long[] { 10 }, t.shape);
             Assert.Equal(torch.float32, t.dtype);
-            Assert.True(torch.tensor(new float[] { 0.564213157f, -0.04519982f, -0.005117342f, 0.395530462f, -0.3780813f, -0.004734449f, -0.3221216f, -0.289159119f, 0.268511474f, 0.180702567f }).allclose(t));
+            Assert.True(torch.tensor(new float[] { 0.564213157f, -0.04519982f, -0.005117342f, 0.395530462f, -0.3780813f, -0.004734449f, -0.3221216f, -0.289159119f, 0.268511474f, 0.180702567f }).allclose(t, rtol: 1e-4, atol: 1e-5));
 
             Assert.Throws<System.Runtime.InteropServices.ExternalException>(() => m.call(torch.ones(100)));
         }