Merge pull request #82 from rapidsai/develop

[REVIEW] merge develop to master and release it as 0.4

docker/build.sh

@@ -2,55 +2,57 @@
 
 echo "Building gQuant container..."
 
-echo -e "Please, select the option which better fits your system configuration:\n" \
-        " - '1' for Ubuntu 16.04 + cuda 9.2\n" \
-        " - '2' for Ubuntu 16.04 + cuda 10.0\n" \
-        " - '3' for Ubuntu 18.04 + cuda 9.2\n" \
-        " - '4' for Ubuntu 18.04 + cuda 10.0"
+echo -e "\nPlease, select your operating system:\n" \
+     " - '1' for Ubuntu 16.04\n" \
+     " - '2' for Ubuntu 18.04\n" \
+     " - '3' for CentOS"
 
-read -p "Enter your option and hit return [1]-4: " SYSTEM_CONFIGURATION
+read -p "Enter your option and hit return [1]-3: " OPERATING_SYSTEM
 
-SYSTEM_CONFIGURATION=${SYSTEM_CONFIGURATION:-1}
-case $SYSTEM_CONFIGURATION in
+OPERATING_SYSTEM=${OPERATING_SYSTEM:-1}
+case $OPERATING_SYSTEM in
     2)
-        echo "Ubuntu 16.04 + cuda 10.0 selected."
-        OS_STR='16.04'
-        CONTAINER_VER='10.0'
-        CUPY='cupy-cuda100'
-        ;;
+	echo "Ubuntu 18.04 selected."
+	OS_STR="ubuntu18.04"
+	;;
     3)
-        echo "Ubuntu 18.04 + cuda 9.2 selected."
-        OS_STR='18.04'
-        CONTAINER_VER='9.2'
-        CUPY='cupy-cuda92'
-        ;;
-    4)
-        echo "Ubuntu 18.04 + cuda 10.0 selected."
-        OS_STR='18.04'
-	CONTAINER_VER='10.0'
-	CUPY='cupy-cuda100'
-        ;;
+	echo "CentOS selected."
+	OS_STR="centos7"
+	;;
     *)
-        echo "Ubuntu 16.04 + cuda 9.2 selected."
-        OS_STR='16.04'
-        CONTAINER_VER='9.2'
-        CUPY='cupy-cuda92'
-        ;;
+	echo "Ubuntu 16.04 selected."
+	OS_STR="ubuntu16.04"
+	;;
 esac
 
-CONTAINER="nvcr.io/nvidia/rapidsai/rapidsai:0.9-cuda${CONTAINER_VER}-runtime-ubuntu${OS_STR}"
+echo -e "\nPlease, select your cuda version:\n" \
+     " - '1' for cuda 9.2\n" \
+     " - '2' for cuda 10.0\n" \
+     " - '3' for cuda 10.1.2"
+
+read -p "Enter your option and hit return [1]-3: " CUDA_VERSION
+
+RAPIDS_VERSION="0.13"
 
-read -p "Would you like to install Vim JupyterLab Extension (optional) [N]/y: " VIM_INSTALL
+CUDA_VERSION=${CUDA_VERSION:-1}
+case $CUDA_VERSION in
+    2)
+	echo "cuda 10.0 selected."
+	CONTAINER_VER='10.0'
+	;;
+    3)
+	echo "cuda 10.1.2 selected."
+	CONTAINER_VER='10.1'
+	;;
+    *)
+	echo "cuda 9.2 selected."
+	CONTAINER_VER='9.2'
+	;;
+esac
 
-VIM_INSTALL=${VIM_INSTALL:-N}
-if [ "$VIM_INSTALL" = "Y" ] || [ "$VIM_INSTALL" = "y" ]; then
-    echo "Vim JupyterLab Extension will be installed."
-else
-    echo "Vim JupyterLab Extension will not be installed."
-fi
+CONTAINER="nvcr.io/nvidia/rapidsai/rapidsai:${RAPIDS_VERSION}-cuda${CONTAINER_VER}-runtime-${OS_STR}"
 
 D_FILE=${D_FILE:='Dockerfile.Rapids'}
-D_CONT=${D_CONT:='gquant/gquant:latest'}
 
 mkdir -p gQuant
 cp -r ../gquant ./gQuant
@@ -60,30 +62,31 @@ cp ../setup.py ./gQuant
 cp ../LICENSE ./gQuant
 rsync -av --progress ../notebooks ./gQuant --exclude data --exclude .cache --exclude many-small --exclude storage --exclude dask-worker-space --exclude __pycache__
 
+gquant_ver=$(grep version gQuant/setup.py | sed "s/^.*version='\([^;]*\)'.*/\1/")
+D_CONT=${D_CONT:="gquant/gquant:${gquant_ver}_${OS_STR}_${CONTAINER_VER}_${RAPIDS_VERSION}"}
+
 cat > $D_FILE <<EOF
 FROM $CONTAINER
 USER root
-
 ADD ./gQuant /rapids/gQuant
-
-RUN apt-get update && apt-get install -y libfontconfig1 libxrender1
-
+RUN if [ "$OS_STR" = "centos7" ]; then \
+        yum install -y fontconfig-devel libXrender ; \
+    else \
+        apt-get update && apt-get install -y libfontconfig1 libxrender1 ; \
+    fi
+# RUN apt-get update && apt-get install -y libfontconfig1 libxrender1
 SHELL ["bash","-c"]
-
 #
 # Additional python libs
 #
-RUN source activate rapids \ 
-    && pip install nxpd $CUPY 
 
 RUN source activate rapids \
     && cd /rapids/gQuant \
     && pip install .
-
 RUN source activate rapids \ 
     && conda install -y -c conda-forge dask-labextension recommonmark numpydoc sphinx_rtd_theme pudb \
-    python-graphviz bqplot=0.11.5 nodejs=11.11.0 jupyterlab=0.35.4 ipywidgets=7.4.2 pytables mkl numexpr
-
+    python-graphviz bqplot=0.11.5 nodejs=11.11.0 jupyterlab=0.35.4 ipywidgets=7.4.2 pytables mkl numexpr \
+    pydot
 #
 # required set up
 #
@@ -92,17 +95,13 @@ RUN source activate rapids \
     && jupyter labextension install [email protected] --no-build \
     && mkdir /.local /.jupyter /.config /.cupy  \
     && chmod 777 /.local /.jupyter /.config /.cupy
-
-RUN if [ "$VIM_INSTALL" = "Y" ] || [ "$VIM_INSTALL" = "y" ]; then /conda/envs/rapids/bin/jupyter labextension install [email protected] --no-build ; fi
-
 RUN source activate rapids \ 
     && jupyter lab build && jupyter lab clean
-
 EXPOSE 8888
 EXPOSE 8787
 EXPOSE 8786
-
 WORKDIR /rapids
+ENTRYPOINT /bin/bash -c 'source activate rapids; /bin/bash'
 EOF
 
 docker build -f $D_FILE -t $D_CONT .

gquant/_common.py

@@ -0,0 +1,15 @@
+from collections import namedtuple, Mapping
+
+__all__ = ['_namedtuple_with_defaults']
+
+
+def _namedtuple_with_defaults(typename, field_names, default_values=()):
+    # https://stackoverflow.com/a/18348004/3457624
+    T = namedtuple(typename, field_names)
+    T.__new__.__defaults__ = (None,) * len(T._fields)
+    if isinstance(default_values, Mapping):
+        prototype = T(**default_values)
+    else:
+        prototype = T(*default_values)
+    T.__new__.__defaults__ = tuple(prototype)
+    return T

gquant/cuindicator/ewm.py

@@ -49,8 +49,8 @@ def kernel(in_arr, out_arr, average_length, span, arr_len, thread_tile,
         for j in range(0, average_length - 1, block_size):
             if (((tx + j) < average_length - 1) and
                     (starting_id - average_length + 1 + tx + j >= 0)):
-                        shared[tx + j] = \
-                            in_arr[starting_id - average_length + 1 + tx + j]
+                shared[tx + j] = \
+                    in_arr[starting_id - average_length + 1 + tx + j]
         cuda.syncthreads()
         # slice the shared memory for each threads
         start_shared = tx * thread_tile
@@ -95,7 +95,7 @@ def __init__(self, span, input_arr, min_periods=None, thread_tile=48,
         if isinstance(input_arr, numba.cuda.cudadrv.devicearray.DeviceNDArray):
             self.gpu_in = input_arr
         else:
-            self.gpu_in = input_arr.data.to_gpu_array()
+            self.gpu_in = input_arr.to_gpu_array()
         if min_periods is None:
             self.min_periods = span
         else:

gquant/cuindicator/frac_diff.py

@@ -189,7 +189,7 @@ def fractional_diff(input_arr, d=0.5, floor=1e-3, min_periods=None,
     if isinstance(input_arr, numba.cuda.cudadrv.devicearray.DeviceNDArray):
         gpu_in = input_arr
     else:
-        gpu_in = input_arr.data.to_gpu_array()
+        gpu_in = input_arr.to_gpu_array()
 
     # compute the weights for the fractional difference
     weights = get_weights_floored(d=d,
@@ -269,6 +269,6 @@ def port_fractional_diff(asset_indicator, input_arr, d=0.5, floor=1e-3,
                                    min_periods=min_periods,
                                    thread_tile=thread_tile,
                                    number_of_threads=number_of_threads)
-    port_mask_nan(asset_indicator.data.to_gpu_array(), out, 0,
+    port_mask_nan(asset_indicator.to_gpu_array(), out, 0,
                   len(weights) - 1)
     return out, weights