GPU

1import numpy as np
2import numba as nb
3from scipy.spatial import cKDTree, distance
4
5# ---------------------------- input data ----------------------------
6""" For testing by prepared files:
7radii = np.load('a.npy')     # shape: (n-spheres, )     must be loaded by np.load('a.npy') or np.loadtxt('radii_large.csv')
8poss = np.load('b.npy')      # shape: (n-spheres, 3)    must be loaded by np.load('b.npy') or np.loadtxt('pos_large.csv', delimiter=',')
9"""
10
11rnd = np.random.RandomState(70)
12data_volume = 200000
13
14radii = rnd.uniform(0.0005, 0.122, data_volume)
15dia_max = 2 * radii.max()
16
17x = rnd.uniform(-1.02, 1.02, (data_volume, 1))
18y = rnd.uniform(-3.52, 3.52, (data_volume, 1))
19z = rnd.uniform(-1.02, -0.575, (data_volume, 1))
20poss = np.hstack((x, y, z))
21# --------------------------------------------------------------------
22
23# @nb.jit('float64[:,::1](float64[:,::1], float64[::1])', forceobj=True, parallel=True)
24def ends_gap(poss, dia_max):
25    particle_corsp_overlaps = np.array([], dtype=np.float64)
26    ends_ind = np.empty([1, 2], dtype=np.int64)
27    """ using list looping """
28    # particle_corsp_overlaps = []
29    # ends_ind = []
30
31    # for particle_idx in nb.prange(len(poss)):  # by list looping
32    for particle_idx in range(len(poss)):
33        unshared_idx = np.delete(np.arange(len(poss)), particle_idx)                                                    # <--- relatively high time consumer
34        poss_without = poss[unshared_idx]
35
36        """ # SCIPY method ---------------------------------------------------------------------------------------------
37        nears_i_ind = cKDTree(poss_without).query_ball_point(poss[particle_idx], r=dia_max)         # <--- high time consumer
38        if len(nears_i_ind) > 0:
39            dist_i, dist_i_ind = cKDTree(poss_without[nears_i_ind]).query(poss[particle_idx], k=len(nears_i_ind))       # <--- high time consumer
40            if not isinstance(dist_i, float):
41                dist_i[dist_i_ind] = dist_i.copy()
42        """  # NUMPY method --------------------------------------------------------------------------------------------
43        lx_limit_idx = poss_without[:, 0] <= poss[particle_idx][0] + dia_max
44        ux_limit_idx = poss_without[:, 0] >= poss[particle_idx][0] - dia_max
45        ly_limit_idx = poss_without[:, 1] <= poss[particle_idx][1] + dia_max
46        uy_limit_idx = poss_without[:, 1] >= poss[particle_idx][1] - dia_max
47        lz_limit_idx = poss_without[:, 2] <= poss[particle_idx][2] + dia_max
48        uz_limit_idx = poss_without[:, 2] >= poss[particle_idx][2] - dia_max
49
50        nears_i_ind = np.where(lx_limit_idx & ux_limit_idx & ly_limit_idx & uy_limit_idx & lz_limit_idx & uz_limit_idx)[0]
51        if len(nears_i_ind) > 0:
52            dist_i = distance.cdist(poss_without[nears_i_ind], poss[particle_idx][None, :]).squeeze()                   # <--- relatively high time consumer
53        # """  # -------------------------------------------------------------------------------------------------------
54            contact_check = dist_i - (radii[unshared_idx][nears_i_ind] + radii[particle_idx])
55            connected = contact_check[contact_check <= 0]
56
57            particle_corsp_overlaps = np.concatenate((particle_corsp_overlaps, connected))
58            """ using list looping """
59            # if len(connected) > 0:
60            #    for value_ in connected:
61            #        particle_corsp_overlaps.append(value_)
62
63            contacts_ind = np.where([contact_check <= 0])[1]
64            contacts_sec_ind = np.array(nears_i_ind)[contacts_ind]
65            sphere_olps_ind = np.where((poss[:, None] == poss_without[contacts_sec_ind][None, :]).all(axis=2))[0]       # <--- high time consumer
66
67            ends_ind_mod_temp = np.array([np.repeat(particle_idx, len(sphere_olps_ind)), sphere_olps_ind], dtype=np.int64).T
68            if particle_idx > 0:
69                ends_ind = np.concatenate((ends_ind, ends_ind_mod_temp))
70            else:
71                ends_ind[0, 0], ends_ind[0, 1] = ends_ind_mod_temp[0, 0], ends_ind_mod_temp[0, 1]
72            """ using list looping """
73            # for contacted_idx in sphere_olps_ind:
74            #    ends_ind.append([particle_idx, contacted_idx])
75
76    # ends_ind_org = np.array(ends_ind)  # using lists
77    ends_ind_org = ends_ind
78    ends_ind, ends_ind_idx = np.unique(np.sort(ends_ind_org), axis=0, return_index=True)                                # <--- relatively high time consumer
79    gap = np.array(particle_corsp_overlaps)[ends_ind_idx]
80    return gap, ends_ind, ends_ind_idx, ends_ind_org
81

1import easyocr
2
3reader = easyocr.Reader(['en'])
4result = reader.readtext('R.png')
5

1import easyocr
2
3reader = easyocr.Reader(['en'])
4result = reader.readtext('R.png')
5CUDA not available - defaulting to CPU. Note: This module is much faster with a GPU.
6
7cv2.error: Unknown C++ exception from OpenCV code
8
9

1@sock.route('/api')
2def echo(sock):
3    while True:
4        # get user input from browser
5        user_input = sock.receive()
6        # print user input on console
7        print(user_input)
8        # read answer from console
9        response = input()
10        # send response to browser
11        sock.send(response)
12

1@sock.route('/api')
2def echo(sock):
3    while True:
4        # get user input from browser
5        user_input = sock.receive()
6        # print user input on console
7        print(user_input)
8        # read answer from console
9        response = input()
10        # send response to browser
11        sock.send(response)
12while True:
13    question = input("")
14    ints = predict(question)
15    answer = response(ints, json_data)
16    print(answer)
17

1@sock.route('/api')
2def echo(sock):
3    while True:
4        # get user input from browser
5        user_input = sock.receive()
6        # print user input on console
7        print(user_input)
8        # read answer from console
9        response = input()
10        # send response to browser
11        sock.send(response)
12while True:
13    question = input("")
14    ints = predict(question)
15    answer = response(ints, json_data)
16    print(answer)
17def predict(sentence):
18    bag_of_words = convert_sentence_in_bag_of_words(sentence)
19    # pass bag as list and get index 0
20    prediction = model.predict(np.array([bag_of_words]))[0]
21    ERROR_THRESHOLD = 0.25
22    accepted_results = [[tag, probability] for tag, probability in enumerate(prediction) if probability > ERROR_THRESHOLD]
23
24    accepted_results.sort(key=lambda x: x[1], reverse=True)
25
26    output = []
27    for accepted_result in accepted_results:
28        output.append({'intent': classes[accepted_result[0]], 'probability': str(accepted_result[1])})
29        print(output)
30    return output
31
32
33def response(intents, json):
34    tag = intents[0]['intent']
35    intents_as_list = json['intents']
36    for i in intents_as_list:
37        if i['tag'] == tag:
38            res = random.choice(i['responses'])
39            break
40    return res
41

1@sock.route('/api')
2def echo(sock):
3    while True:
4        # get user input from browser
5        user_input = sock.receive()
6        # print user input on console
7        print(user_input)
8        # read answer from console
9        response = input()
10        # send response to browser
11        sock.send(response)
12while True:
13    question = input("")
14    ints = predict(question)
15    answer = response(ints, json_data)
16    print(answer)
17def predict(sentence):
18    bag_of_words = convert_sentence_in_bag_of_words(sentence)
19    # pass bag as list and get index 0
20    prediction = model.predict(np.array([bag_of_words]))[0]
21    ERROR_THRESHOLD = 0.25
22    accepted_results = [[tag, probability] for tag, probability in enumerate(prediction) if probability > ERROR_THRESHOLD]
23
24    accepted_results.sort(key=lambda x: x[1], reverse=True)
25
26    output = []
27    for accepted_result in accepted_results:
28        output.append({'intent': classes[accepted_result[0]], 'probability': str(accepted_result[1])})
29        print(output)
30    return output
31
32
33def response(intents, json):
34    tag = intents[0]['intent']
35    intents_as_list = json['intents']
36    for i in intents_as_list:
37        if i['tag'] == tag:
38            res = random.choice(i['responses'])
39            break
40    return res
41 * Running on http://127.0.0.1:5000/ (Press CTRL+C to quit)
42 * Restarting with stat
43 * Serving Flask app 'server' (lazy loading)
44 * Environment: production
45   WARNING: This is a development server. Do not use it in a production deployment.
46   Use a production WSGI server instead.
47 * Debug mode: on
48

1@sock.route('/api')
2def echo(sock):
3    while True:
4        # get user input from browser
5        user_input = sock.receive()
6        # print user input on console
7        print(user_input)
8        # read answer from console
9        response = input()
10        # send response to browser
11        sock.send(response)
12while True:
13    question = input("")
14    ints = predict(question)
15    answer = response(ints, json_data)
16    print(answer)
17def predict(sentence):
18    bag_of_words = convert_sentence_in_bag_of_words(sentence)
19    # pass bag as list and get index 0
20    prediction = model.predict(np.array([bag_of_words]))[0]
21    ERROR_THRESHOLD = 0.25
22    accepted_results = [[tag, probability] for tag, probability in enumerate(prediction) if probability > ERROR_THRESHOLD]
23
24    accepted_results.sort(key=lambda x: x[1], reverse=True)
25
26    output = []
27    for accepted_result in accepted_results:
28        output.append({'intent': classes[accepted_result[0]], 'probability': str(accepted_result[1])})
29        print(output)
30    return output
31
32
33def response(intents, json):
34    tag = intents[0]['intent']
35    intents_as_list = json['intents']
36    for i in intents_as_list:
37        if i['tag'] == tag:
38            res = random.choice(i['responses'])
39            break
40    return res
41 * Running on http://127.0.0.1:5000/ (Press CTRL+C to quit)
42 * Restarting with stat
43 * Serving Flask app 'server' (lazy loading)
44 * Environment: production
45   WARNING: This is a development server. Do not use it in a production deployment.
46   Use a production WSGI server instead.
47 * Debug mode: on
482022-02-13 11:31:38.887640: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:305] Could not identify NUMA node of platform GPU ID 0, defaulting to 0. Your kernel may not have been built with NUMA support.
492022-02-13 11:31:38.887734: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:271] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 0 MB memory) -> physical PluggableDevice (device: 0, name: METAL, pci bus id: <undefined>)
50Metal device set to: Apple M1
51
52systemMemory: 16.00 GB
53maxCacheSize: 5.33 GB
54

1name: N
2
3channels:
4  - defaults
5  - conda-forge
6
7dependencies:
8  - python=3.9
9  - cudatoolkit
10  - cudnn
11

1name: N
2
3channels:
4  - defaults
5  - conda-forge
6
7dependencies:
8  - python=3.9
9  - cudatoolkit
10  - cudnn
11[tool.poetry]
12name = "N"
13authors = ["B"]
14
15[tool.poetry.dependencies]
16python = "3.9"
17torch = "^1.10.1"
18
19[build-system]
20requires = ["poetry-core>=1.0.0"]
21build-backend = "poetry.core.masonry.api"
22

1Uncaught TypeError: Cannot read properties of undefined (reading 'getCurrentWindow')
2

1Uncaught TypeError: Cannot read properties of undefined (reading 'getCurrentWindow')
2[14880:1207/145651.085:ERROR:gpu_init.cc(457)] Passthrough is not supported, GL is disabled, ANGLE is
3

1import cv2
2import mediapipe as mp
3import time
4
5inFile = '/dev/video0'
6
7capture = cv2.VideoCapture(inFile)
8FramesVideo = int(capture.get(cv2.CAP_PROP_FRAME_COUNT)) # Number of frames inside video
9FrameCount = 0 # Currently playing frame
10prevTime = 0
11
12# some objects for mediapipe
13mpPose = mp.solutions.pose
14mpDraw = mp.solutions.drawing_utils
15pose = mpPose.Pose()
16
17while True:
18    FrameCount += 1
19    #read image and convert to rgb
20    success, img = capture.read()
21    imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
22    
23    #process image
24    results = pose.process(imgRGB)
25
26    if results.pose_landmarks:
27        mpDraw.draw_landmarks(img, results.pose_landmarks, mpPose.POSE_CONNECTIONS)
28        #get landmark positions
29        landmarks = []
30        for id, lm in enumerate(results.pose_landmarks.landmark):
31            h, w, c = img.shape 
32            cx, cy = int(lm.x * w), int(lm.y * h) 
33            cv2.putText(img, str(id), (cx,cy), cv2.FONT_HERSHEY_PLAIN, 1, (255,0,0), 1)
34            landmarks.append((cx,cy))
35 
36    # calculate and print fps
37    frameTime = time.time()
38    fps = 1/(frameTime-prevTime)
39    prevTime = frameTime
40    cv2.putText(img, str(int(fps)), (30,50), cv2.FONT_HERSHEY_PLAIN, 3, (255,0,0), 3)
41
42    #show image
43    cv2.imshow('Video', img)
44    cv2.waitKey(1)
45    if FrameCount == FramesVideo-1:
46        capture.release()
47        cv2.destroyAllWindows()
48        break
49

1$ wget https://developer.download.nvidia.com/compute/cuda/repos/wsl-ubuntu/x86_64/cuda-wsl-ubuntu.pin
2$ sudo mv cuda-wsl-ubuntu.pin /etc/apt/preferences.d/cuda-repository-pin-600
3$ wget https://developer.download.nvidia.com/compute/cuda/11.4.0/local_installers/cuda-repo-wsl-ubuntu-11-4-local_11.4.0-1_amd64.deb
4$ sudo dpkg -i cuda-repo-wsl-ubuntu-11-4-local_11.4.0-1_amd64.deb
5$ sudo apt-key add /var/cuda-repo-wsl-ubuntu-11-4-local/7fa2af80.pub
6$ sudo apt-get update
7$ sudo apt-get -y install cuda
8

1$ wget https://developer.download.nvidia.com/compute/cuda/repos/wsl-ubuntu/x86_64/cuda-wsl-ubuntu.pin
2$ sudo mv cuda-wsl-ubuntu.pin /etc/apt/preferences.d/cuda-repository-pin-600
3$ wget https://developer.download.nvidia.com/compute/cuda/11.4.0/local_installers/cuda-repo-wsl-ubuntu-11-4-local_11.4.0-1_amd64.deb
4$ sudo dpkg -i cuda-repo-wsl-ubuntu-11-4-local_11.4.0-1_amd64.deb
5$ sudo apt-key add /var/cuda-repo-wsl-ubuntu-11-4-local/7fa2af80.pub
6$ sudo apt-get update
7$ sudo apt-get -y install cuda
8$ nvidia-smi
9Failed to initialize NVML: GPU access blocked by the operating system
10Failed to properly shut down NVML: GPU access blocked by the operating system
11

1$ wget https://developer.download.nvidia.com/compute/cuda/repos/wsl-ubuntu/x86_64/cuda-wsl-ubuntu.pin
2$ sudo mv cuda-wsl-ubuntu.pin /etc/apt/preferences.d/cuda-repository-pin-600
3$ wget https://developer.download.nvidia.com/compute/cuda/11.4.0/local_installers/cuda-repo-wsl-ubuntu-11-4-local_11.4.0-1_amd64.deb
4$ sudo dpkg -i cuda-repo-wsl-ubuntu-11-4-local_11.4.0-1_amd64.deb
5$ sudo apt-key add /var/cuda-repo-wsl-ubuntu-11-4-local/7fa2af80.pub
6$ sudo apt-get update
7$ sudo apt-get -y install cuda
8$ nvidia-smi
9Failed to initialize NVML: GPU access blocked by the operating system
10Failed to properly shut down NVML: GPU access blocked by the operating system
11PS C:\WINDOWS\system32> nvidia-smi
12Wed Nov 17 21:46:50 2021
13+-----------------------------------------------------------------------------+
14| NVIDIA-SMI 510.06       Driver Version: 510.06       CUDA Version: 11.6     |
15|-------------------------------+----------------------+----------------------+
16| GPU  Name            TCC/WDDM | Bus-Id        Disp.A | Volatile Uncorr. ECC |
17| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
18|                               |                      |               MIG M. |
19|===============================+======================+======================|
20|   0  NVIDIA GeForce ... WDDM  | 00000000:01:00.0 Off |                  N/A |
21| N/A   44C    P8    N/A /  N/A |     75MiB /  4096MiB |      1%      Default |
22|                               |                      |                  N/A |
23+-------------------------------+----------------------+----------------------+
24
25+-----------------------------------------------------------------------------+
26| Processes:                                                                  |
27|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
28|        ID   ID                                                   Usage      |
29|=============================================================================|
30|  No running processes found                                                 |
31+-----------------------------------------------------------------------------+
32

1$ wget https://developer.download.nvidia.com/compute/cuda/repos/wsl-ubuntu/x86_64/cuda-wsl-ubuntu.pin
2$ sudo mv cuda-wsl-ubuntu.pin /etc/apt/preferences.d/cuda-repository-pin-600
3$ wget https://developer.download.nvidia.com/compute/cuda/11.4.0/local_installers/cuda-repo-wsl-ubuntu-11-4-local_11.4.0-1_amd64.deb
4$ sudo dpkg -i cuda-repo-wsl-ubuntu-11-4-local_11.4.0-1_amd64.deb
5$ sudo apt-key add /var/cuda-repo-wsl-ubuntu-11-4-local/7fa2af80.pub
6$ sudo apt-get update
7$ sudo apt-get -y install cuda
8$ nvidia-smi
9Failed to initialize NVML: GPU access blocked by the operating system
10Failed to properly shut down NVML: GPU access blocked by the operating system
11PS C:\WINDOWS\system32> nvidia-smi
12Wed Nov 17 21:46:50 2021
13+-----------------------------------------------------------------------------+
14| NVIDIA-SMI 510.06       Driver Version: 510.06       CUDA Version: 11.6     |
15|-------------------------------+----------------------+----------------------+
16| GPU  Name            TCC/WDDM | Bus-Id        Disp.A | Volatile Uncorr. ECC |
17| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
18|                               |                      |               MIG M. |
19|===============================+======================+======================|
20|   0  NVIDIA GeForce ... WDDM  | 00000000:01:00.0 Off |                  N/A |
21| N/A   44C    P8    N/A /  N/A |     75MiB /  4096MiB |      1%      Default |
22|                               |                      |                  N/A |
23+-------------------------------+----------------------+----------------------+
24
25+-----------------------------------------------------------------------------+
26| Processes:                                                                  |
27|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
28|        ID   ID                                                   Usage      |
29|=============================================================================|
30|  No running processes found                                                 |
31+-----------------------------------------------------------------------------+
32PS C:\WINDOWS\system32> nvidia-smi -q
33
34==============NVSMI LOG==============
35
36Timestamp                                 : Wed Nov 17 21:48:19 2021
37Driver Version                            : 510.06
38CUDA Version                              : 11.6
39
40Attached GPUs                             : 1
41GPU 00000000:01:00.0
42    Product Name                          : NVIDIA GeForce GTX 1050
43    Product Brand                         : GeForce
44    Product Architecture                  : Pascal
45    Display Mode                          : Disabled
46    Display Active                        : Disabled
47    Persistence Mode                      : N/A
48    MIG Mode
49        Current                           : N/A
50        Pending                           : N/A
51    Accounting Mode                       : Disabled
52    Accounting Mode Buffer Size           : 4000
53    Driver Model
54        Current                           : WDDM
55        Pending                           : WDDM
56    Serial Number                         : N/A
57    GPU UUID                              : GPU-7645072f-7516-5488-316d-6277d101f64e
58    Minor Number                          : N/A
59    VBIOS Version                         : 86.07.3e.00.1c
60    MultiGPU Board                        : No
61    Board ID                              : 0x100
62    GPU Part Number                       : N/A
63    Module ID                             : 0
64    Inforom Version
65        Image Version                     : N/A
66        OEM Object                        : N/A
67        ECC Object                        : N/A
68        Power Management Object           : N/A
69    GPU Operation Mode
70        Current                           : N/A
71        Pending                           : N/A
72    GSP Firmware Version                  : N/A
73    GPU Virtualization Mode
74        Virtualization Mode               : None
75        Host VGPU Mode                    : N/A
76    IBMNPU
77        Relaxed Ordering Mode             : N/A
78    PCI
79        Bus                               : 0x01
80        Device                            : 0x00
81        Domain                            : 0x0000
82        Device Id                         : 0x1C8D10DE
83        Bus Id                            : 00000000:01:00.0
84        Sub System Id                     : 0x07BE1028
85        GPU Link Info
86            PCIe Generation
87                Max                       : 3
88                Current                   : 3
89            Link Width
90                Max                       : 16x
91                Current                   : 16x
92        Bridge Chip
93            Type                          : N/A
94            Firmware                      : N/A
95        Replays Since Reset               : 0
96        Replay Number Rollovers           : 0
97        Tx Throughput                     : 0 KB/s
98        Rx Throughput                     : 0 KB/s
99    Fan Speed                             : N/A
100    Performance State                     : P8
101    Clocks Throttle Reasons
102        Idle                              : Active
103        Applications Clocks Setting       : Not Active
104        SW Power Cap                      : Not Active
105        HW Slowdown                       : Not Active
106            HW Thermal Slowdown           : Not Active
107            HW Power Brake Slowdown       : Not Active
108        Sync Boost                        : Not Active
109        SW Thermal Slowdown               : Not Active
110        Display Clock Setting             : Not Active
111    FB Memory Usage
112        Total                             : 4096 MiB
113        Used                              : 75 MiB
114        Free                              : 4021 MiB
115    BAR1 Memory Usage
116        Total                             : 256 MiB
117        Used                              : 2 MiB
118        Free                              : 254 MiB
119    Compute Mode                          : Default
120    Utilization
121        Gpu                               : 0 %
122        Memory                            : 0 %
123        Encoder                           : 0 %
124        Decoder                           : 0 %
125    Encoder Stats
126        Active Sessions                   : 0
127        Average FPS                       : 0
128        Average Latency                   : 0
129    FBC Stats
130        Active Sessions                   : 0
131        Average FPS                       : 0
132        Average Latency                   : 0
133    Ecc Mode
134        Current                           : N/A
135        Pending                           : N/A
136    ECC Errors
137        Volatile
138            Single Bit
139                Device Memory             : N/A
140                Register File             : N/A
141                L1 Cache                  : N/A
142                L2 Cache                  : N/A
143                Texture Memory            : N/A
144                Texture Shared            : N/A
145                CBU                       : N/A
146                Total                     : N/A
147            Double Bit
148                Device Memory             : N/A
149                Register File             : N/A
150                L1 Cache                  : N/A
151                L2 Cache                  : N/A
152                Texture Memory            : N/A
153                Texture Shared            : N/A
154                CBU                       : N/A
155                Total                     : N/A
156        Aggregate
157            Single Bit
158                Device Memory             : N/A
159                Register File             : N/A
160                L1 Cache                  : N/A
161                L2 Cache                  : N/A
162                Texture Memory            : N/A
163                Texture Shared            : N/A
164                CBU                       : N/A
165                Total                     : N/A
166            Double Bit
167                Device Memory             : N/A
168                Register File             : N/A
169                L1 Cache                  : N/A
170                L2 Cache                  : N/A
171                Texture Memory            : N/A
172                Texture Shared            : N/A
173                CBU                       : N/A
174                Total                     : N/A
175    Retired Pages
176        Single Bit ECC                    : N/A
177        Double Bit ECC                    : N/A
178        Pending Page Blacklist            : N/A
179    Remapped Rows                         : N/A
180    Temperature
181        GPU Current Temp                  : 40 C
182        GPU Shutdown Temp                 : 102 C
183        GPU Slowdown Temp                 : 97 C
184        GPU Max Operating Temp            : 78 C
185        GPU Target Temperature            : N/A
186        Memory Current Temp               : N/A
187        Memory Max Operating Temp         : N/A
188    Power Readings
189        Power Management                  : N/A
190        Power Draw                        : N/A
191        Power Limit                       : N/A
192        Default Power Limit               : N/A
193        Enforced Power Limit              : N/A
194        Min Power Limit                   : N/A
195        Max Power Limit                   : N/A
196    Clocks
197        Graphics                          : 0 MHz
198        SM                                : 0 MHz
199        Memory                            : 405 MHz
200        Video                             : 0 MHz
201    Applications Clocks
202        Graphics                          : N/A
203        Memory                            : N/A
204    Default Applications Clocks
205        Graphics                          : N/A
206        Memory                            : N/A
207    Max Clocks
208        Graphics                          : 1911 MHz
209        SM                                : 1911 MHz
210        Memory                            : 3504 MHz
211        Video                             : 1708 MHz
212    Max Customer Boost Clocks
213        Graphics                          : N/A
214    Clock Policy
215        Auto Boost                        : N/A
216        Auto Boost Default                : N/A
217    Voltage
218        Graphics                          : N/A
219    Processes                             : None
220

1GPU available: False, used: False
2TPU available: False, using: 0 TPU cores
3IPU available: False, using: 0 IPUs
4