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Ich habe eine lmdb-Datenbank für Eingaben und eine weitere für Etiketten erstellt.Caffe LeNet Fehlerprüfung fehlgeschlagen: shape [i]> = 0 (-1 vs. 0)
Die Eingabeform ist (3,3,1226) und die Bezeichnung sind (1,11226), also (C, H, W).
Wenn der folgende Code ausgeführt:
import caffe
caffe.set_device(0)
caffe.set_mode_gpu()
solver = caffe.SGDSolver('my_lenet_solver.prototxt')
ich diese Fehlermeldungen bekommen:
I0527 23:40:39.806207 551 layer_factory.hpp:77] Creating layer data
I0527 23:40:39.807922 551 net.cpp:106] Creating Layer data
I0527 23:40:39.807942 551 net.cpp:411] data -> data
I0527 23:40:39.808825 570 db_lmdb.cpp:38] Opened lmdb train_x
I0527 23:40:39.830607 551 data_layer.cpp:41] output data size: 35,3,3,1226
I0527 23:40:39.835955 551 base_data_layer.cpp:69] Initializing prefetch
I0527 23:40:39.836031 551 base_data_layer.cpp:72] Prefetch initialized.
I0527 23:40:39.836050 551 net.cpp:150] Setting up data
I0527 23:40:39.836071 551 net.cpp:157] Top shape: 35 3 3 1226 (386190)
I0527 23:40:39.836074 551 net.cpp:165] Memory required for data: 1544760
I0527 23:40:39.836097 551 layer_factory.hpp:77] Creating layer label
I0527 23:40:39.836238 551 net.cpp:106] Creating Layer label
I0527 23:40:39.836254 551 net.cpp:411] label -> label
I0527 23:40:39.837540 572 db_lmdb.cpp:38] Opened lmdb train_y
I0527 23:40:39.838732 551 data_layer.cpp:41] output data size: 35,1,1,1226
I0527 23:40:39.840147 551 base_data_layer.cpp:69] Initializing prefetch
I0527 23:40:39.840224 551 base_data_layer.cpp:72] Prefetch initialized.
I0527 23:40:39.840236 551 net.cpp:150] Setting up label
I0527 23:40:39.840263 551 net.cpp:157] Top shape: 35 1 1 1226 (42910)
I0527 23:40:39.840272 551 net.cpp:165] Memory required for data: 1716400
I0527 23:40:39.840286 551 layer_factory.hpp:77] Creating layer conv1
I0527 23:40:39.840348 551 net.cpp:106] Creating Layer conv1
I0527 23:40:39.840363 551 net.cpp:454] conv1 <- data
I0527 23:40:39.840409 551 net.cpp:411] conv1 -> conv1
I0527 23:40:39.841969 571 data_layer.cpp:102] Prefetch batch: 4 ms.
I0527 23:40:39.842005 571 data_layer.cpp:103] Read time: 0.076 ms.
I0527 23:40:39.842010 571 data_layer.cpp:104] Transform time: 3.263 ms.
I0527 23:40:39.842770 576 data_layer.cpp:102] Prefetch batch: 0 ms.
I0527 23:40:39.842788 576 data_layer.cpp:103] Read time: 0.06 ms.
I0527 23:40:39.842793 576 data_layer.cpp:104] Transform time: 0.472 ms.
I0527 23:40:39.845005 576 data_layer.cpp:102] Prefetch batch: 0 ms.
I0527 23:40:39.845021 576 data_layer.cpp:103] Read time: 0.063 ms.
I0527 23:40:39.845031 576 data_layer.cpp:104] Transform time: 0.566 ms.
I0527 23:40:39.846081 576 data_layer.cpp:102] Prefetch batch: 0 ms.
I0527 23:40:39.846099 576 data_layer.cpp:103] Read time: 0.058 ms.
I0527 23:40:39.846107 576 data_layer.cpp:104] Transform time: 0.593 ms.
I0527 23:40:39.846982 571 data_layer.cpp:102] Prefetch batch: 3 ms.
I0527 23:40:39.847000 571 data_layer.cpp:103] Read time: 0.048 ms.
I0527 23:40:39.847005 571 data_layer.cpp:104] Transform time: 2.707 ms.
I0527 23:40:39.861234 571 data_layer.cpp:102] Prefetch batch: 7 ms.
I0527 23:40:39.861282 571 data_layer.cpp:103] Read time: 0.083 ms.
I0527 23:40:39.861294 571 data_layer.cpp:104] Transform time: 4.307 ms.
F0527 23:40:40.031951 551 blob.cpp:32] Check failed: shape[i] >= 0 (-1 vs. 0)
*** Check failure stack trace: ***
Mein Zug protobuf ist:
layer {
name: "data"
type: "Data"
top: "data"
transform_param {
scale: 0.00392156862745
}
data_param {
source: "train_x"
batch_size: 35
backend: LMDB
}
}
layer {
name: "label"
type: "Data"
top: "label"
transform_param {
scale: 0.00392156862745
}
data_param {
source: "train_y"
batch_size: 35
backend: LMDB
}
}
layer {
name: "conv1"
type: "Convolution"
bottom: "data"
top: "conv1"
convolution_param {
num_output: 20
kernel_size: 5
weight_filler {
type: "xavier"
}
}
}
layer {
name: "pool1"
type: "Pooling"
bottom: "conv1"
top: "pool1"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
name: "conv2"
type: "Convolution"
bottom: "pool1"
top: "conv2"
convolution_param {
num_output: 50
kernel_size: 5
weight_filler {
type: "xavier"
}
}
}
layer {
name: "pool2"
type: "Pooling"
bottom: "conv2"
top: "pool2"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
name: "fc1"
type: "InnerProduct"
bottom: "pool2"
top: "fc1"
inner_product_param {
num_output: 500
weight_filler {
type: "xavier"
}
}
}
layer {
name: "relu1"
type: "ReLU"
bottom: "fc1"
top: "fc1"
}
layer {
name: "score"
type: "InnerProduct"
bottom: "fc1"
top: "score"
inner_product_param {
num_output: 1226
weight_filler {
type: "xavier"
}
}
}
layer {
name: "loss"
type: "SoftmaxWithLoss"
bottom: "score"
bottom: "label"
top: "loss"
}
Ich weiß nicht, was falsch ist um diesen Fehler zu bekommen. Könnte ich nicht eine Eingabe mit drei Zeilen und eine Beschriftung nur mit einer Zeile haben?
Vielen Dank!