fix softmax activation for large values

test/activations/activations.js

@@ -52,6 +52,22 @@ describe('activations', function () {
       assert.deepEqual(t.tensor.shape, shapeExpected)
       assert.isTrue(approxEquals(t.tensor, dataExpected))
     })
+
+    it('[activations.softmax.2] should work for very large values', function () {
+      const key = 'activations.softmax.2'
+      console.log(`\n%c[${key}] 1D, large values`, styles.h3)
+      let t = new KerasJS.Tensor(TEST_DATA[key].input.data, TEST_DATA[key].input.shape)
+      console.log('%cin', styles.h4, stringifyCondensed(t.tensor))
+      const startTime = performance.now()
+      activations.softmax(t)
+      const endTime = performance.now()
+      console.log('%cout', styles.h4, stringifyCondensed(t.tensor))
+      logTime(startTime, endTime)
+      const dataExpected = new Float32Array(TEST_DATA[key].expected.data)
+      const shapeExpected = TEST_DATA[key].expected.shape
+      assert.deepEqual(t.tensor.shape, shapeExpected)
+      assert.isTrue(approxEquals(t.tensor, dataExpected))
+    })
   })
 
   /*********************************************************

test/activations/data_activations.js

@@ -12,6 +12,10 @@
       input: { data: [0, 0.2, 0.5, -0.1, 1, 2, -0.03, 0.3, 0, 0.8, -0.3, 1], shape: [2, 6] },
       expected: { data: [0.067194, 0.082071, 0.110784, 0.0608, 0.182652, 0.4965, 0.107768, 0.149902, 0.11105, 0.247147, 0.082268, 0.301865], shape: [2, 6] }
     },
+    'activations.softmax.2': {
+      input: { data: [0, 0.2, 0.5, -0.1, 1, 90], shape: [6] },
+      expected: { data: [0.0, 0.0, 0.0, 0.0, 0.0, 1.0], shape: [6] }
+    },
     'activations.softplus.0': {
       input: { data: [0, 0.2, 0.5, -0.1, 1, 2], shape: [6] },
       expected: { data: [0.693147, 0.798139, 0.974077, 0.644397, 1.313262, 2.126928], shape: [6] }