"remove python side test case to another PR."

python/paddle/v2/framework/tests/test_nccl_allreduce_op.py

@@ -1,97 +0,0 @@
-import unittest, os
-from threading import Thread
-import numpy as np
-import paddle.v2 as paddle
-from paddle.v2.framework.op import Operator
-import paddle.v2.framework.core as core
-from op_test import OpTest, create_op, set_input
-
-# gpu_list = os.environ["NV_LIST"]
-gpu_list = "0,1,2,3"
-
-if not core.is_compile_gpu() or not gpu_list:
-    exit(0)
-
-g_scope = core.Scope()
-g_ctx = core.DeviceContext.create(core.CPUPlace())
-gpus = [int(g) for g in gpu_list.split(",")]
-
-
-# ground truth
-def allreduce(tensors, gpus):
-    num_device = len(gpus)
-    assert (len(tensors) == num_device), "not match of tensor and device"
-    Out = tensors
-    for i in range(1, len(tensors)):
-        Out[0] += Out[i]
-
-    for i in range(1, len(tensors)):
-        Out[i] = Out[0]
-
-    return Out
-
-
-input_data = [
-    np.random.random((32, 32)).astype("float32") for i in range(len(gpus))
-]
-output_data = allreduce(input_data, gpus)
-
-
-def thread_allreduce_op(thread_id, gpu_id):
-    i = gpu_id
-    scope = g_scope.new_scope()
-    place = core.GPUPlace(gpus[i])
-    inputs = {
-        "X": input_data[i],
-        "Communicator": scope.find_var("Communicator")
-    }
-    outputs = {"Out": output_data[i]}
-
-    op = create_op(scope, "ncclAllReduce", inputs, outputs, attrs={})
-    place = core.GPUPlace(gpus[i])
-    set_input(scope, op, inputs, place)
-
-    ctx = core.DeviceContext.create(place)
-
-    print "thread_id : ", thread_id, "gpu_id : ", gpu_id, " invoke allreduce"
-    op.run(scope, ctx)
-    print "thread_id : ", thread_id, "gpu_id : ", gpu_id, " allreduce Done."
-
-
-class TestNCCLAllReduce(unittest.TestCase):
-    def setUp(self):
-        self.op_type = "ncclAllReduce"
-
-        nccl_init = create_op(
-            g_scope,
-            op_type="ncclInit",
-            inputs={},
-            outputs={
-                "Communicator": g_scope.var("Communicator").get_communicator()
-            },
-            attrs={"gpus": gpus})
-        nccl_init.run(g_scope, g_ctx)
-
-    def test_output(self):
-        ops = []
-        for i in range(len(gpus)):
-            th = Thread(
-                target=thread_allreduce_op, args=(
-                    i,
-                    gpus[i], ))
-            th.start()
-            ops.append(th)
-        for t in ops:
-            t.join()
-
-        idx = 0
-        for out_name, out_dup in Operator.get_op_outputs(self.op_type):
-            actual = np.array(g_scope.find_var(out_name).get_tensor())
-            expect = output_data[idx]
-
-            idx += 1
-            self.assertTrue(actual, expect), "has diff"
-
-
-if __name__ == "__main__":
-    unittest.main()

python/paddle/v2/framework/tests/test_nccl_reduce_op.py

@@ -1,25 +0,0 @@
-import unittest, os
-import numpy as np
-import paddle.v2 as paddle
-from paddle.v2.framework.op import Operator
-import paddle.v2.framework.core as core
-from op_test import OpTest, create_op, set_input
-
-gpu_list = "0,1,2,3"
-g_scope = core.Scope()
-g_ctx = core.DeviceContext.create(core.CPUPlace())
-
-if not core.is_compile_gpu() or not gpu_list:
-    exit(0)
-
-
-class TestNCCLReduce(OpTest):
-    def setUp(self):
-        self.op_type = "ncclReduce"
-        self.gpus = [int(g) for g in gpu_list.split(",")]
-
-        self.scope = g_scope.var("Communicator").get_communicator()
-        self.outputs = {"Communicator": self.scope.var("Communicator")}
-
-    def test_check_output(self):
-        self.check_output()