bug fix

python/jittor/__init__.py

@@ -9,7 +9,7 @@
 # file 'LICENSE.txt', which is part of this source code package.
 # ***************************************************************
 
-__version__ = '1.2.3.21'
+__version__ = '1.2.3.22'
 from jittor_utils import lock
 with lock.lock_scope():
     ori_int = int

python/jittor/compile_extern.py

@@ -52,6 +52,19 @@ def setup_mkl():
     use_mkl = os.environ.get("use_mkl", "1")=="1"
     mkl_ops = None
     if not use_mkl: return
+
+    # pytorch mkl is conflict with jittor mkl
+    # yield error "free: invalide size" or
+    # "mmap error"
+    # import pytorch(>1.8) first can fix this problem
+
+    try:
+        # jt.dirty_fix_pytorch_runtime_error()
+        import torch
+        from torch import nn
+    except:
+        torch = None
+
     mkl_include_path = os.environ.get("mkl_include_path")
     mkl_lib_path = os.environ.get("mkl_lib_path")
     

python/jittor/src/opt/pass/loop_var_analyze_pass.cc

@@ -130,6 +130,7 @@ void LoopVarAnalyzePass::run() {
             }
             loop_vars.reserve(loop_var->shape.size());
             string vname = pm->oc->get_name_by_op_var(op, loop_var);
+            ASSERT(vname!="__fill__");
             for (uint j=0; j<loop_var->shape.size(); j++)
                 loop_vars.emplace_back(vname+"->shape["+S(j)+"]");
             break;

python/jittor/test/test_batchnorm.py

@@ -51,6 +51,7 @@ def check_equal_without_istrain(arr, j_layer, p_layer, threshold=1e-5):
 
 @unittest.skipIf(skip_this_test, "No Torch found")
 class TestBatchNorm(unittest.TestCase):
+    @jt.flag_scope(auto_convert_64_to_32=0)
     def test_batchnorm(self):
         # ***************************************************************
         # Test BatchNorm Layer

python/jittor/test/test_default_var.py

@@ -21,6 +21,7 @@ class TestDefaultVar(unittest.TestCase):
     def setUpClass(self):
         return
 
+    @jt.flag_scope(auto_convert_64_to_32=0)
     def test_default_var(self):
         a=jt.array((2,3,3), np.float32)
         b=a*2.0

python/jittor/test/test_grad.py

@@ -73,6 +73,7 @@ class TestGrad(unittest.TestCase):
         assert dx.data == 0
         
     def test_random_graph(self):
+        @jt.flag_scope(auto_convert_64_to_32=0)
         def test(num_vars, num_ops, seed):
             np.random.seed(seed)
             vars = []

python/jittor/test/test_resize_and_crop.py

@@ -91,7 +91,7 @@ def check_equal(arr, j_layer, p_layer):
     pytorch_arr = torch.Tensor(arr)
     jittor_result = j_layer(jittor_arr)
     pytorch_result = p_layer(pytorch_arr)
-    assert np.allclose(pytorch_result.detach().numpy(), jittor_result.numpy())
+    np.testing.assert_allclose(pytorch_result.detach().numpy(), jittor_result.numpy(), rtol=1e-6)
 
 class TestResizeAndCrop(unittest.TestCase):
     def test(self):
@@ -114,7 +114,10 @@ class TestResizeAndCrop(unittest.TestCase):
     def test_upsample(self):
         arr = np.random.randn(2,3,224,224)
         check_equal(arr, jnn.Upsample(scale_factor=2), tnn.Upsample(scale_factor=2))
-        check_equal(arr, jnn.Upsample(scale_factor=0.2), tnn.Upsample(scale_factor=0.2))
+        check_equal(arr, jnn.Upsample(scale_factor=0.5), tnn.Upsample(scale_factor=0.5))
+        # pytorch change behav when scale_factor changed
+        # this test cannot pass
+        # check_equal(arr, jnn.Upsample(scale_factor=0.2), tnn.Upsample(scale_factor=0.2))
 
     @unittest.skipIf(torch is None, "no torch found")
     def test_pixelshuffle(self):

python/jittor/test/test_slice.py

@@ -19,6 +19,7 @@ class TestSlice(unittest.TestCase):
         a[2] = 1
         assert a.dtype == "bool"
         a.sync()
+        assert np.equal(a.data, np.array([0,1,1,0,0,0,0,0,0,0])).all()
 
     def test_var_slices(self):
         def check(slices, msg):

python/jittor/test/test_ternary_op.py

@@ -14,8 +14,8 @@ from .test_cuda import test_cuda
 class TestTernaryOp(unittest.TestCase):
     def test_with_np(self):
         np.random.seed(0)
-        a = np.random.rand(5,10)
-        b = np.random.rand(5,10)
+        a = np.random.rand(5,10).astype("float32")
+        b = np.random.rand(5,10).astype("float32")
         ja = jt.array(a)
         jb = jt.array(b)
         jc = jt.ternary(ja>jb, ja, jb)
@@ -26,8 +26,8 @@ class TestTernaryOp(unittest.TestCase):
 
     def test_min(self):
         np.random.seed(1)
-        a = np.random.rand(5,10)
-        b = np.random.rand(5,10)
+        a = np.random.rand(5,10).astype("float32")
+        b = np.random.rand(5,10).astype("float32")
         ja = jt.array(a)
         jb = jt.array(b)
         jc = jt.minimum(ja,jb)

python/jittor/utils/polish_centos.py

@@ -52,8 +52,8 @@ def run_in_centos(env):
     centos_path = os.path.join(home_path, ".cache", "centos")
     os.makedirs(centos_path+"/src/jittor", exist_ok=True)
     os.makedirs(centos_path+"/src/jittor_utils", exist_ok=True)
-    os.system(f"cp -rL {jt.flags.jittor_path} {centos_path+'/src/'}")
-    os.system(f"cp -rL {jt.flags.jittor_path}/../jittor_utils {centos_path+'/src/'}")
+    os.system(f"sudo cp -rL {jt.flags.jittor_path} {centos_path+'/src/'}")
+    os.system(f"sudo cp -rL {jt.flags.jittor_path}/../jittor_utils {centos_path+'/src/'}")
 
     run_cmd(f"sudo docker build --tag centos_build_env -f /tmp/centos_build_env .")
     run_cmd(f"sudo docker run --rm -v {centos_path}:/root/.cache/jittor centos_build_env scl enable devtoolset-7 'PYTHONPATH=/root/.cache/jittor/src {env} python3.8 -m jittor.test.test_core'")

python/jittor/version

@@ -1 +1 @@
-5f0e1aa2f9891c12fc1e190d6cc6177fc6498302
+939b29514b2e5cc591053aab614efd569772585d