Implement tanh and exp in Numpy_intrinsic library

integration_tests/CMakeLists.txt

@@ -174,6 +174,8 @@ RUN(NAME elemental_03        LABELS cpython llvm)
 RUN(NAME elemental_04        LABELS cpython llvm)
 RUN(NAME elemental_05        LABELS cpython llvm)
 RUN(NAME elemental_06        LABELS cpython llvm)
+RUN(NAME elemental_07        LABELS cpython llvm)
+RUN(NAME elemental_08        LABELS cpython llvm)
 RUN(NAME test_random         LABELS cpython llvm)
 RUN(NAME test_os             LABELS cpython llvm)
 RUN(NAME test_builtin        LABELS cpython llvm)

integration_tests/elemental_07.py

@@ -0,0 +1,50 @@
+from ltypes import i32, f64, f32
+from numpy import empty, tanh, reshape, int32, float64, sin, log10
+
+def verify1d(array: f32[:], result: f32[:], size: i32):
+    i: i32
+    eps: f32 = 1e-6
+
+    for i in range(size):
+        assert abs(tanh(sin(array[i])) - result[i]) <= eps
+
+def verifynd(array: f64[:, :, :, :], result: f64[:, :, :, :], size1: i32, size2: i32, size3: i32, size4: i32):
+    i: i32; size: i32;
+    eps: f64 = 1e-12
+    shape: i32[1] = empty((1,), dtype=int32)
+    size = size1 * size2 * size3 * size4
+    shape[0] = size
+    array1d: f64[1024] = reshape(array, shape)
+    result1d: f64[1024] = reshape(result, shape)
+
+    for i in range(size):
+        assert abs((tanh(sin(array1d[i])) + 2)/2 - result1d[i]) <= eps
+
+
+def elemental_tanh():
+    i: i32; j: i32; k: i32; l: i32; size: i32;
+
+    array1d: f32[80] = empty(80)
+    tanh1d: f32[80] = empty(80)
+
+    for i in range(80):
+        array1d[i] = i / 10.0
+
+    tanh1d = tanh(sin(array1d))
+    verify1d(array1d, tanh1d, 10)
+
+    arraynd: f64[16, 8, 4, 2] = empty((16, 8, 4, 2))
+    tanhnd: f64[16, 8, 4, 2] = empty((16, 8, 4, 2))
+    size = 16 * 8 * 4 * 2
+
+    for i in range(16):
+        for j in range(8):
+            for k in range(4):
+                for l in range(2):
+                    arraynd[i, j, k, l] = float(i + 2*j + 3*k + 4*k)/size
+
+    tanhnd = (tanh(sin(arraynd)) + 2)/2
+
+    verifynd(arraynd, tanhnd, 16, 8, 4, 2)
+
+elemental_tanh()

integration_tests/elemental_08.py

@@ -0,0 +1,49 @@
+from ltypes import i32, f64, f32
+from numpy import empty, reshape, int32, exp
+
+def verify1d(array: f32[:], result: f32[:], size: i32):
+    i: i32
+    eps: f32 = 1e-6
+
+    for i in range(size):
+        assert abs(exp(array[i]) - result[i]) <= eps
+
+def verifynd(array: f64[:, :, :, :], result: f64[:, :, :, :], size1: i32, size2: i32, size3: i32, size4: i32):
+    i: i32; size: i32;
+    eps: f64 = 1e-12
+    shape: i32[1] = empty((1,), dtype=int32)
+    size = size1 * size2 * size3 * size4
+    shape[0] = size
+    array1d: f64[1024] = reshape(array, shape)
+    result1d: f64[1024] = reshape(result, shape)
+
+    for i in range(size):
+        assert abs(( exp(array1d[i]) + exp(array1d[i] / 3) ) / 2 - result1d[i]) <= eps
+
+def elemental_exp():
+    i: i32; j: i32; k: i32; l: i32; size: i32;
+
+    array1d: f32[80] = empty(80)
+    exp1d: f32[80] = empty(80)
+
+    for i in range(80):
+        array1d[i] = i / 50.0
+
+    exp1d = exp(array1d)
+    verify1d(array1d, exp1d, 80)
+
+    arraynd: f64[16, 8, 4, 2] = empty((16, 8, 4, 2))
+    expnd: f64[16, 8, 4, 2] = empty((16, 8, 4, 2))
+    size = 32
+
+    for i in range(16):
+        for j in range(8):
+            for k in range(4):
+                for l in range(2):
+                    arraynd[i, j, k, l] = float( i / 8 + j / 4 + k / 2 + l ) / size
+
+    expnd = (exp(arraynd) + exp(arraynd / 3)) / 2
+
+    verifynd(arraynd, expnd, 16, 8, 4, 2)
+
+elemental_exp()

src/runtime/lpython_intrinsic_numpy.py

@@ -207,3 +207,44 @@ def _lfortran_sacos(x: f32) -> f32:
 @vectorize
 def arccos(x: f32) -> f32:
     return _lfortran_sacos(x)
+
+########## tanh ##########
+
+@ccall
+def _lfortran_dtanh(x: f64) -> f64:
+    pass
+
+@overload
+@vectorize
+def tanh(x: f64) -> f64:
+    return _lfortran_dtanh(x)
+
+@ccall
+def _lfortran_stanh(x: f32) -> f32:
+    pass
+
+@overload
+@vectorize
+def tanh(x: f32) -> f32:
+    return _lfortran_stanh(x)
+
+########## exp ##########
+
+@ccall
+def _lfortran_dexp(x: f64) -> f64:
+    pass
+
+@overload
+@vectorize
+def exp(x: f64) -> f64:
+    return _lfortran_dexp(x)
+
+@ccall
+def _lfortran_sexp(x: f32) -> f32:
+    pass
+
+@overload
+@vectorize
+def exp(x: f32) -> f32:
+    return _lfortran_sexp(x)
+

tests/reference/asr-array_01_decl-39cf894.json

@@ -6,7 +6,7 @@
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     "outfile_hash": null,
     "stdout": "asr-array_01_decl-39cf894.stdout",
-    "stdout_hash": "5ecf6039e91c9a83a28aeb6a43fdc4d72d9561a3d8f0542ccdf019a3",
+    "stdout_hash": "581cac2fa1b5469cf1d1ccb3a91fb97ce22413a9b7a3bcb25b5e634c",
     "stderr": null,
     "stderr_hash": null,
     "returncode": 0

tests/reference/asr-array_02_decl-e8f6874.json

@@ -6,7 +6,7 @@
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     "outfile_hash": null,
     "stdout": "asr-array_02_decl-e8f6874.stdout",
-    "stdout_hash": "4a38b14377eb0d1bb08af1a3ac8298d87507a01528f564d6c2c77ed0",
+    "stdout_hash": "8086f9d4d75d8ac5b7819ddc6fa3f7066865eadffe0ad0a77bb3472b",
     "stderr": null,
     "stderr_hash": null,
     "returncode": 0

tests/reference/asr-elemental_01-b58df26.json

@@ -6,7 +6,7 @@
     "outfile": null,
     "outfile_hash": null,
     "stdout": "asr-elemental_01-b58df26.stdout",
-    "stdout_hash": "90ca8c75d86ea830fb2083b6b5a6813f385c634015b3e890784d6b2e",
+    "stdout_hash": "572b8546d87ba877caf44a4126b22b93a28cee853c0d5a56e89b8720",
     "stderr": null,
     "stderr_hash": null,
     "returncode": 0

tests/reference/asr-test_numpy_03-e600a49.json

@@ -6,7 +6,7 @@
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     "outfile_hash": null,
     "stdout": "asr-test_numpy_03-e600a49.stdout",
-    "stdout_hash": "47bb384882382f1812820016fd01fa30b8f04c52dd50c731c27b741c",
+    "stdout_hash": "1db5a5bf604257b691bc633d1e56383142498365050933be5df2a1a5",
     "stderr": null,
     "stderr_hash": null,
     "returncode": 0

tests/reference/asr-test_numpy_04-ecbb614.json

@@ -6,7 +6,7 @@
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     "outfile_hash": null,
     "stdout": "asr-test_numpy_04-ecbb614.stdout",
-    "stdout_hash": "52f53b0d09f443f7fcceb3db59b0bcf943f525a8746783bebb6980bb",
+    "stdout_hash": "92ccd61ff99f3f3187821f5adfaf4e84e3264ea14aa6ad7618e41aa3",
     "stderr": null,
     "stderr_hash": null,
     "returncode": 0

tests/reference/asr-vec_01-66ac423.json

@@ -6,7 +6,7 @@
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     "outfile_hash": null,
     "stdout": "asr-vec_01-66ac423.stdout",
-    "stdout_hash": "27e2d720253a51fcc8522c2c43f572c4fc1d55adf4b351eb407867fe",
+    "stdout_hash": "4210bc49a30dcc6f81bce09c613c5a6515f2d9bcd311ccba2d8cc895",
     "stderr": null,
     "stderr_hash": null,
     "returncode": 0

tests/reference/pass_loop_vectorise-vec_01-be9985e.json

@@ -6,7 +6,7 @@
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     "outfile_hash": null,
     "stdout": "pass_loop_vectorise-vec_01-be9985e.stdout",
-    "stdout_hash": "5e63d66337232a414c2dcc035de82b554cd346fe7d579429deddb397",
+    "stdout_hash": "90114a0b77cfbb8d9d18385e27a6393ca56659a19440dacf7d0cddca",
     "stderr": null,
     "stderr_hash": null,
     "returncode": 0