Hi,

We have tested the tf.nn.sigmoid() op with TensorRT but cannot reproduce this issue.

Please remember to convert the input to **np.float32** to reserve full precision.

```
data = data.astype(np.float32)
```

Here is our testing code for your reference:

```
from tensorrt.parsers import uffparser
import tensorflow as tf
import tensorrt as trt
import pycuda.driver as cuda
import numpy as np
import uff
MAX_WORKSPACE = 1 << 20
MAX_BATCHSIZE = 1
G_LOGGER = trt.infer.ConsoleLogger(trt.infer.LogSeverity.INFO)
inputs = tf.placeholder(dtype=tf.float32, shape=[1,10])
output = tf.nn.sigmoid(inputs, name='out')
data = np.expand_dims(np.array([8.879764, -8.724520, -10.623482, -11.822342, -12.868923, -11.805139, -13.092369, -11.573037, -11.112819, -11.025951]), axis=0)
data = data.astype(np.float32)
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
tf_result = sess.run(output,feed_dict={inputs:data})
graphdef = tf.get_default_graph().as_graph_def()
frozen_graph = tf.graph_util.convert_variables_to_constants(sess, graphdef, ['out'])
tf_model = tf.graph_util.remove_training_nodes(frozen_graph)
uff_model = uff.from_tensorflow(tf_model, ['out'])
parser = uffparser.create_uff_parser()
parser.register_input("Placeholder", (1,10,1), 0)
parser.register_output("out")
engine = trt.utils.uff_to_trt_engine(G_LOGGER, uff_model, parser, MAX_BATCHSIZE, MAX_WORKSPACE)
parser.destroy()
runtime = trt.infer.create_infer_runtime(G_LOGGER)
context = engine.create_execution_context()
trt_result = cuda.pagelocked_empty(10, dtype=np.float32)
d_input = cuda.mem_alloc(10 * data.dtype.itemsize)
d_output = cuda.mem_alloc(10 * trt_result.dtype.itemsize)
bindings = [int(d_input), int(d_output)]
stream = cuda.Stream()
cuda.memcpy_htod_async(d_input, data, stream)
context.enqueue(1, bindings, stream.handle, None)
cuda.memcpy_dtoh_async(trt_result, d_output, stream)
print('TensorFlow:')
print(tf_result)
print('\nTensorRT:')
print(trt_result)
```

Thanks.